Fluid component analysis system and method for glucose monitoring and control

ABSTRACT

Disclosed are methods and apparatus for determining analyte concentration in a sample such as bodily fluid. Systems and methods disclosed herein can also include a treatment dosing system to infuse or inject a treatment drug (e.g. insulin or glucose) and provide glycemic control. The dose of the treatment drug may be based on the concentration of the analyte or the average value for the concentration of the analyte and/or the rate of change of the value of the concentration of the analyte.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit under 35 U.S.C. §119(e) of U.S.Provisional Patent Application No. 60/979,044, entitled “System and UserInterface For Infusion and Analysis,” filed Oct. 10, 2007; U.S.Provisional Patent Application No. 60/979,380, entitled “Fluid ComponentAnalysis System and Bolus Injection,” filed Oct. 11, 2007; U.S.Provisional Patent Application No. 61/025,260, entitled “Fluid ComponentAnalysis System and Method for Glucose Monitoring and Control,” filedJan. 31, 2008; U.S. Provisional Patent Application No. 60/979,348,entitled “System and Method for Glucose Monitoring and Control,” filedOct. 11, 2007; U.S. Provisional Patent Application No. 61/096,461,entitled “Analyte Monitoring System and Treatment Dosing Protocol,”filed Sep. 12, 2008; and U.S. Provisional Patent Application No.61/099,491, entitled “An Analyte Monitoring System Including a TreatmentDosing Assistant,” filed Sep. 23, 2008. Each of the foregoingapplications, as well as U.S. Provisional Patent Application No.60/978,385, entitled “Dilution Calibration for an Analyte DetectionSystem,” filed Oct. 8, 2007, is hereby incorporated by reference in itsentirety and made part of this specification.

BACKGROUND

1. Field

Some embodiments of the disclosure relate generally to methods anddevices for determining a concentration of an analyte in a sample, suchas an analyte in a sample of bodily fluid, as well as methods anddevices which can be used to support the making of such determinations.This disclosure also relates generally to a user interface for use withsuch apparatus. Some embodiments of this disclosure also relategenerally to bolus injection and basal infusion systems and relatedapparatus. Some embodiments in this disclosure also relate to an analytedetection system configured to provide glycemic control and/or TightGlycemic Control (TGC). Some aspects of this disclosure relate to ananalyte detection system that is configured to determine a dosingprotocol based on one or more measurements of the concentration of ananalyte. Some aspects of this disclosure relate to a system and methodthat provides feedback to a healthcare provider regarding the treatmentdose being administered to the patient. Some aspects of this disclosurealso relate generally to systems and methods for calibrating analyteconcentration when dilution of the sample has occurred.

2. Description of Related Art

It is advantageous to measure the levels of certain analytes, such asglucose, in a bodily fluid, such as blood). This can be done, forexample, in a hospital or clinical setting when there is a risk that thelevels of certain analytes may move outside a desired range, which inturn can jeopardize the health of a patient. Systems for measuringanalyte levels may include a user interface (UI) that permits a usersuch as, for example, a patient, a health care provider, and so forth,to interact with the system. Currently known systems for analytemonitoring in a hospital or clinical setting may suffer from variousdrawbacks.

SUMMARY

Example embodiments described herein have several features, no singleone of which is indispensible or solely responsible for their desirableattributes. Without limiting the scope of the claims, some of theadvantageous features will now be summarized.

Embodiments of an analyte detection and treatment dosing systemcomprising a fluid transport network configured to provide fluidcommunication with a body fluid in a patient through a patient end aredisclosed. The disclosed embodiments can further comprise at least onepump system coupled to the fluid transport network, the pump systemhaving a sampling mode in which the pump system is operable to withdrawa sample of bodily fluid from the patient end and transport said sampleof bodily fluid toward the body fluid analyzer, and an infusion mode inwhich the pump system is operable to transport an infusion fluid to thepatient. The disclosed embodiments can further comprise a body fluidanalyzer accessible via the fluid transport network, the body fluidanalyzer configured to measure a characteristic of at least one analytein the body fluid and determine the concentration of the at least oneanalyte from the measured characteristic; and a treatment dosing systemin communication with the body fluid analyzer, said treatment dosingsystem including a treatment dosing protocol stored in a computer memoryand configured to automatically determine a recommended dose of aninfusion substance configured to provide glycemic control, wherein thebody fluid analyzer determines the recommended dose based at least inpart on the measured concentration of the analyte and the storedtreatment dosing protocol, wherein the treatment dosing systemcomprising a treatment pump having a variable pump rate to deliver therecommended dose of the infusion substance to the patient.

Embodiments of an analyte detection and treatment dosing systemcomprising a fluid transport network configured to provide fluidcommunication with a body fluid in a patient through a patient end aredisclosed. Disclosed embodiments comprise at least one pump systemcoupled to the fluid transport network, the pump system having asampling mode in which the pump system is operable to withdraw a sampleof bodily fluid from the patient end and transport said sample of bodilyfluid towards the body fluid analyzer, and an infusion mode in which thepump system is operable to transport an infusion fluid to the patient.The disclosed embodiments also comprise a body fluid analyzer accessiblevia the fluid transport network, the body fluid analyzer configured tomeasure a characteristic of at least one analyte in the body fluid anddetermine the concentration of the at least one analyte from themeasured characteristic; and a treatment dosing system in communicationwith the body fluid analyzer, said treatment dosing system including atreatment dosing protocol stored in a computer memory and configured toautomatically determine a recommended dose of an infusion substanceconfigured to provide glycemic control, wherein the recommended dose isdetermined based at least in part on one or more determinations by thebody fluid analyzer of the concentration of the analyte and thetreatment dosing protocol. In some embodiments, the treatment dosingsystem comprises a basal delivery system and a bolus injection system,both systems configured to deliver infusion substances to the patientthrough said patient end and through the same intravenous access line.

Embodiments of an analyte detection and control system to determine andregulate the concentration of one or more analytes in a sample of bodilyfluid are disclosed. The disclosed embodiments, can comprise a controlsystem, an analyte detector configured to measure a characteristic of atleast one analyte in the sample of bodily fluid and determine aconcentration of the analyte in the sample based on the measuredcharacteristic, a fluid handling system operatively coupled to theanalyte detector, said fluid handling system comprising a fluidpassageway in communication with a patient through a patient end, a pumpunit configured to engage the fluid handling system and draw a sample ofbodily fluid from the patient periodically at draw intervals of lessthan 1 hour for analysis, a source of infusion fluid configured toadjust glycemic levels in the patient, said infusion fluid source influid communication with the fluid handling system and a treatmentdosing system in communication with the body fluid analyzer, saidtreatment dosing system including a treatment dosing protocol andconfigured to determine a recommended dose for the infusion fluid,wherein the recommended dose is determined based at least in part on oneor more determinations by the body fluid analyzer of the concentrationof the analyte and the treatment dosing protocol.

An embodiment of a method of analyzing an analyte in the body fluid of apatient is disclosed. The method comprises placing a body fluid analyzerin fluid communication with the body fluid in the patient; transportinga sample of the body fluid toward the body fluid analyzer; with the bodyfluid analyzer, measuring a characteristic of an analyte in the bodilyfluid and determining the concentration of the analyte in the bodyfluid, while the analyzer is in fluid communication with the body fluidin the patient; and with a treatment dosing system in communication withthe body fluid analyzer, determining a recommended dose for an infusionfluid based at least in part on one or more determinations by the bodyfluid analyzer of the concentration of the analyte and a treatmentdosing protocol.

An embodiment of a method of monitoring and regulating the concentrationof one or more analytes in a sample of bodily fluid is disclosed. Themethod comprises providing a fluid connection to a patient; periodicallywithdrawing a certain volume of bodily fluid from the patient at drawintervals of less than 1 hour; sensing a property of the withdrawn fluidusing one or more sensors; dividing the withdrawn volume of fluid intoan analysis portion and a return portion; measuring a characteristic ofsaid analysis portion to determine the concentration of an analyte insaid analysis portion; determining a recommended dose for an infusionfluid for an infusion fluid based at least in part on one or moredeterminations by the body fluid analyzer of the concentration of theanalyte and a treatment dosing protocol; and providing an instruction toan infusion fluid system to infuse the recommended dose of infusionfluid into the patient at a prescribed infusion fluid delivery rate.

Embodiments of an analyte detection and treatment dosing system aredisclosed. Disclosed embodiments comprise a fluid transport networkconfigured to provide fluid communication with a body fluid in apatient; a body fluid analyzer accessible via the fluid transportnetwork, the body fluid analyzer configured to measure a characteristicof at least one analyte in the body fluid and determine theconcentration of the at least one analyte from the measuredcharacteristic; a treatment dosing system in communication with the bodyfluid analyzer, said treatment dosing system including a treatmentdosing protocol and configured to determine a recommended dose for aninfusion fluid configured to provide glycemic control, wherein therecommended dose is determined based at least in part on one or moredeterminations by the body fluid analyzer of the concentration of theanalyte and the treatment dosing protocol; a treatment pump coupled tothe fluid transport network, the treatment pump operable to transportthe infusion fluid to the patient through the patient end; and a fluidsystem controller comprising a graphic user interface, said fluid systemcontroller configured to actuate the treatment pump and control the pumprate of the pump, wherein the fluid system controller and the body fluidanalyzer are both included within a single housing, the graphic userinterface is located on the same housing, and the graphic user interfaceis configured to display the determined analyte concentration and therecommended dose. In some embodiments, the graphic user interfaceincludes an input element configured to accept user input, the userinterface further configured to adjust the actual dose of the infusionfluid based at least in part on the user input. In some embodiments thegraphic user interface is configured to display both the recommendeddose and the actual dose, where both the recommended dose and the actualdose are expressed as infusion rates. In some embodiments, the graphicuser interface includes an input element configured to accept userinput, the user interface configured to actuate the pump unit based atleast in part on the user input.

Embodiments of an analyte monitoring system comprising a fluidic systemin fluid communication with a source of bodily fluid, said fluidicsystem being configured to obtain a sample of bodily fluid from thesource; an analyte detection system configured to analyze the sample ofbodily fluid or a component of the sample of bodily fluid; and a fluidinfusion system are disclosed. In some disclosed embodiments, theanalyte detection system is configured to determine the concentration ofan analyte in said sample of the bodily fluid or a component of thesample of the bodily fluid. In some embodiments, the analyte detectionsystem is configured to access a measurement database and calculate anaverage concentration of the analyte based on the determinedconcentration and one or more previous values for the concentration ofthe analyte stored in the measurement database.

Embodiments of an analyte monitoring system comprising a fluidic systemin fluid communication with a source of bodily fluid, said fluidicsystem being configured to obtain a first sample of bodily fluid fromthe source at a first time; an analyte detection system configured toanalyze the first sample of bodily fluid or a component of the firstsample of bodily fluid; and a fluid infusion system are disclosed. Insome embodiments, the analyte detection system is configured todetermine the concentration of an analyte in said first sample of thebodily fluid or a component of the first sample of the bodily fluid andstore the value of the determined concentration in a measurementdatabase. In some disclosed embodiments, the fluidic system furtherobtains a second sample of the bodily fluid at a second time andpresents said second sample to the analyte detection system foranalysis. In the disclosed embodiments, the analyte detection systemanalyzes the second sample or a component of the second sample anddetermines the concentration of the analyte in the second sample or thecomponent of the second sample, calculates a rate of change of theconcentration of the analyte and determines a treatment dose based onthe rate of change of the concentration of the analyte if theconcentration of the analyte in the second sample is not within aprescribed range. In some embodiments, the analyte detection systemcommunicates with the fluid infusion system to deliver the determinedtreatment dose.

Embodiments of an analyte monitoring system comprising a fluidic systemin fluid communication with a source of bodily fluid, said fluidicsystem being configured to obtain a sample of bodily fluid from thesource several times in a give time interval are disclosed. Somedisclosed embodiments can comprise an analyte detection systemconfigured to analyze the sample of bodily fluid or a component of thesample of bodily fluid and determine the concentration of an analyte insaid sample of the bodily fluid or a component of the sample of thebodily fluid, wherein the analyte detection system is further configuredto access a measurement history and store the estimated concentration ofthe analyte in the measurement history. Some disclosed embodimentscomprise a feedback system; and a user interface configured to accept aninput from a user; wherein the feedback system calculates a predictedvalue for the concentration of the analyte at a future time based on theinput from the user and one or more previous values for theconcentration of the analyte stored in the measurement history, andwherein the feedback system alerts the user through the user interfaceif the predicted value for the concentration is not within an acceptablerange.

Embodiments of an analyte monitoring system comprising a fluidic systemin fluid communication with a source of bodily fluid, said fluidicsystem being configured to obtain a sample of bodily fluid from thesource several times in a give time interval are disclosed. Thedisclosed embodiments further comprise an analyte detection systemconfigured to analyze the sample of bodily fluid or a component of thesample of bodily fluid and determine the concentration of an analyte insaid sample of the bodily fluid or a component of the sample of thebodily fluid, wherein the analyte detection system is further configuredto access a measurement history and store the estimated concentration ofthe analyte in the measurement history. The disclosed embodiments canalso comprise a fluid infusion system comprising a plurality of infusionfluid sources, each infusion fluid source configured to provide one ormore drugs or chemicals; a user feedback system; a watch list comprisinga catalog of spectra related to various known substances that maypresent medical hazards, alone or in combination, the watch list beingelectronically accessible to the user feedback system; and a userinterface configured to provide information to a user and accept inputfrom the user. In some embodiments, the feedback system is configured toobtain one or more spectroscopic measurements of the contents of theplurality of infusion fluid sources, compare the spectroscopicmeasurements with the watch list, and alert the user through the userinterface if any substance in the watch list is detected in theplurality of infusion fluid sources.

Embodiments of a combined glucose monitoring and adjustment systemcomprising a fluid control device with pumps, valves, and fluidpassageways configured to draw fluid from a fluid source and deliver aportion of that fluid to an analyte monitoring system are disclosed. Thedisclosed embodiments can further comprise an optical glucose meterconfigured to irradiate the fluid or a portion thereof and detectsecondary radiation, either transmitted or reflected, and determine,based on that secondary radiation, a concentration of an analyte in thefluid. The disclosed embodiments can further comprise a glucoseadjustment system. In some embodiments, the glucose adjustment systemcan comprise a repository of a treatment substance selected from thegroup consisting of insulin and a sugar; a pump configured to adjust thelevel of glucose in the fluid source by infusing insulin and/or sugar;and a controller configured to control the pump. In some embodiments,the body fluid analyzer is configured for calibration no more than twiceper day. In some embodiments, the body fluid analyzer is configured forcalibration no more than once per day. In some embodiments, the bodyfluid analyzer is configured for calibration no more than once every 36hours. In some embodiments, the body fluid analyzer is configured forcalibration no more than once every two days. In some embodiments, thebody fluid analyzer is configured for calibration no more than onceevery three days.

BRIEF DESCRIPTION OF THE DRAWINGS

The following drawings and the associated descriptions are provided toillustrate embodiments of the present disclosure and do not limit thescope of the claims.

FIG. 1 shows an embodiment of an apparatus for withdrawing and analyzingfluid samples.

FIG. 2 illustrates how various other devices can be supported on or nearan embodiment of apparatus illustrated in FIG. 1.

FIG. 3 illustrates an embodiment of the apparatus in FIG. 1 configuredto be connected to a patient.

FIG. 3A illustrates an embodiment of the apparatus in FIG. 1 that is notconfigured to be connected to a patient but which receives a fluidsample from an extracorporeal fluid container such as, for example, atest tube. This embodiment of the apparatus can advantageously providein vitro analysis of a fluid sample.

FIG. 4 is a block diagram of an embodiment of a system for withdrawingand analyzing fluid samples.

FIG. 5 schematically illustrates an embodiment of a fluid system thatcan be part of a system for withdrawing and analyzing fluid samples.

FIG. 6 schematically illustrates another embodiment of a fluid systemthat can be part of a system for withdrawing and analyzing fluidsamples.

FIG. 7 is an oblique schematic depiction of an embodiment of amonitoring device.

FIG. 8 shows a cut-away side view of an embodiment of a monitoringdevice.

FIG. 9 shows a cut-away perspective view of an embodiment of amonitoring device.

FIG. 10 illustrates an embodiment of a removable cartridge that caninterface with a monitoring device.

FIG. 11 illustrates an embodiment of a fluid routing card that can bepart of the removable cartridge of FIG. 10.

FIG. 12 illustrates how non-disposable actuators can interface with thefluid routing card of FIG. 11.

FIG. 13 illustrates a modular pump actuator connected to a syringehousing that can form a portion of a removable cartridge.

FIG. 14 shows a rear perspective view of internal scaffolding and somepinch valve pump bodies.

FIG. 15 shows an underneath perspective view of a sample cell holderattached to a centrifuge interface, with a view of an interface with asample injector.

FIG. 16 shows a plan view of a sample cell holder with hidden and/ornon-surface portions illustrated using dashed lines.

FIG. 17 shows a top perspective view of the centrifuge interfaceconnected to the sample holder.

FIG. 18 shows a perspective view of an example optical system.

FIG. 19 shows a filter wheel that can be part of the optical system ofFIG. 18.

FIG. 20 schematically illustrates an embodiment of an optical systemthat comprises a spectroscopic analyzer adapted to measure spectra of afluid sample.

FIG. 21 is a flowchart that schematically illustrates an embodiment of amethod for estimating the concentration of an analyte in the presence ofinterferents.

FIG. 22 is a flowchart that schematically illustrates an embodiment of amethod for performing a statistical comparison of the absorptionspectrum of a sample with the spectrum of a sample population andcombinations of individual library interferent spectra.

FIG. 23 is a flowchart that schematically illustrates an exampleembodiment of a method for estimating analyte concentration in thepresence of the possible interferents.

FIGS. 23A through 23D illustrate different examples of the resultsobtained by using various algorithms to estimate the concentration of ananalyte in a sample.

FIGS. 24 and 25 schematically illustrate the visual appearance ofembodiments of a user interface for a system for withdrawing andanalyzing fluid samples.

FIG. 26 schematically depicts various components and/or aspects of apatient monitoring system and the relationships among the componentsand/or aspects.

FIG. 27 is a flowchart that schematically illustrates an embodiment of amethod of providing glycemic control.

FIG. 28A schematically illustrates the visual appearance of anembodiment of a display graphic for providing information related tosuggested and actual insulin dose for a patient.

FIGS. 28B-28F schematically illustrate embodiments of a display graphiccomprising a graphic user interface and illustrate examples of numericaldisplay mode, trend display mode, suggested and actual insulin doseinformation, and controls for delivery of insulin.

FIG. 29 is a flowchart that schematically illustrates an embodiment of amethod of determining a treatment dose based on the averageconcentration of an analyte.

FIG. 30 is a flowchart that schematically illustrates an embodiment of amethod of determining a treatment dose based on the rate of change ofthe concentration of an analyte.

FIG. 31A is a flowchart that schematically illustrates an embodiment ofa method of determining a treatment dose based on the averageconcentration of an analyte and the rate of change of the concentrationof the analyte.

FIG. 31B is a flowchart that schematically illustrates an embodiment ofa method of determining a treatment dose based on the currentconcentration of an analyte and the rate of change of the concentrationof the analyte.

FIG. 32 schematically illustrates an embodiment of a history that storesthe previously determined values for the concentration of an analyte andthe values for a treatment dose previously administered.

FIG. 33 is a flowchart that schematically illustrates steps in a methodof providing feedback regarding a treatment dose.

FIG. 34 schematically depicts a feedback system and the relationshipbetween the feedback system and the other components and/or aspects ofthe patient monitoring system.

FIG. 35 schematically illustrates an embodiment of a fluid system thatcan be part of a system for withdrawing and analyzing fluid samples andcalibrating the analyzed samples for sample dilution;

FIG. 36 schematically illustrates another embodiment of a fluid systemthat can be part of a system for withdrawing and analyzing fluid samplesand calibrating the analyzed samples for sample dilution; and

FIG. 37 is a flowchart that schematically illustrates an embodiment of amethod for calibrating an analyte measurement in a fluid sample foreffects of dilution of the fluid sample.

These and other features will now be described with reference to thedrawings summarized above. The drawings and the associated descriptionsare provided to illustrate embodiments and not to limit the scope of anyclaim. Throughout the drawings, reference numbers may be reused toindicate correspondence between referenced elements. In addition, whereapplicable, the first one or two digits of a reference numeral for anelement can frequently indicate the figure number in which the elementfirst appears.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

Although certain preferred embodiments and examples are disclosed below,inventive subject matter extends beyond the specifically disclosedembodiments to other alternative embodiments and/or uses and tomodifications and equivalents thereof. Thus, the scope of the claimsappended hereto is not limited by any of the particular embodimentsdescribed below. For example, in any method or process disclosed herein,the acts or operations of the method or process may be performed in anysuitable sequence and are not necessarily limited to any particulardisclosed sequence. Various operations may be described as multiplediscrete operations in turn, in a manner that may be helpful inunderstanding certain embodiments; however, the order of descriptionshould not be construed to imply that these operations are orderdependent. Additionally, the structures, systems, and/or devicesdescribed herein may be embodied as integrated components or as separatecomponents. For purposes of comparing various embodiments, certainaspects and advantages of these embodiments are described. Notnecessarily all such aspects or advantages are achieved by anyparticular embodiment. Thus, for example, various embodiments may becarried out in a manner that achieves or optimizes one advantage orgroup of advantages as taught herein without necessarily achieving otheraspects or advantages as may also be taught or suggested herein.

The systems and methods discussed herein can be used anywhere,including, for example, in laboratories, hospitals, healthcarefacilities, intensive care units (ICUs), or residences. Moreover, thesystems and methods discussed herein can be used for invasivetechniques, as well as non-invasive techniques or techniques that do notinvolve a body or a patient such as, for example, in vitro techniques.

Analyte Monitoring Apparatus

FIG. 1 shows an embodiment of an apparatus 100 for withdrawing andanalyzing fluid samples. The apparatus 100 includes a monitoring device102. In some embodiments, the monitoring device 102 can be an“OptiScanner®” monitor available from OptiScan Biomedical Corporation ofHayward, Calif. In some embodiments, the device 102 can measure one ormore physiological parameters, such as the concentration of one or moresubstance(s) in a sample fluid. The sample fluid can be, for example,whole blood from a patient 302 (see, e.g., FIG. 3) and/or a component ofwhole blood such as, e.g., blood plasma. In some embodiments, the device100 can also deliver an infusion fluid to a patient.

In the illustrated embodiment, the monitoring device 102 includes adisplay 104 such as, for example, a touch-sensitive liquid crystaldisplay. The display 104 can provide an interface that includes alerts,indicators, charts, and/or soft buttons. The device 102 also can includeone or more inputs and/or outputs 106 that provide connectivity and/orpermit user interactivity.

In the embodiment shown in FIG. 1, the device 102 is mounted on a stand108. The stand 108 may comprise a cart such as, for example, a wheeledcart 130 as shown in FIG. 1. In some embodiments, the stand 108 isconfigured to roll on a wheeled pedestal 240 (shown in FIG. 2). Thestand 108 advantageously can be easily moved and includes one or morepoles 110 and/or hooks 112. The poles 110 and hooks 112 can beconfigured to accommodate other medical devices and/or implements,including, for example, infusion pumps, saline bags, arterial pressuresensors, other monitors and medical devices, and so forth. Some standsor carts may become unstable if intravenous (IV) bags, IV pumps, andother medical devices are hung too high on the stand or cart. In someembodiments, the apparatus 100 can be configured to have a low center ofgravity, which may overcome possible instability. For example, the stand108 can be weighted at the bottom to at least partially offset theweight of IV bags, IV pumps and medical devices that may be attached tothe hooks 112 that are placed above the monitoring device 102. Addingweight toward the bottom (e.g., near the wheels) may help prevent theapparatus 100 from tipping over.

In some embodiments, the apparatus 100 includes the cart 130, which hasan upper shelf 131 on which the monitoring device 102 may be placed (orattached) and a bottom shelf 132 on which a battery 134 may be placed(or attached). The battery 134 may be used as a main or backup powersupply for the monitoring device 102 (which may additionally oralternatively accept electrical power from a wall socket). Two or morebatteries are used in certain embodiments. The apparatus 100 may beconfigured so that the upper and lower shelves 131, 132 are close toground level, and the battery provides counterweight. Other types ofcounterweights may be used. For example, in some embodiments, portionsof the cart 130 near the floor (e.g., a lower shelf) are weighted,formed from a substantial quantity of material (e.g., thick sheets ofmetal), and/or formed from a relatively high-density metal (e.g., lead).In some embodiments the bottom shelf 132 is approximately 6 inches to 1foot above ground level, and the upper shelf 131 is approximately 2 feetto 4 feet above ground level. In some embodiments the upper shelf 131may be configured to support approximately 40 pounds (lbs), and thebottom shelf 132 may be configured to support approximately 20 lbs. Onepossible advantage of embodiments having such a configuration is that IVpumps, bags containing saline, blood and/or drugs, and other medicalequipment weighing approximately 60 lbs, collectively, can be hung onthe hooks 112 above the shelves without making the apparatus 100unstable. The apparatus 100 may be moved by applying a horizontal forceon the apparatus 100, for example, by pushing and/or pulling the poles110. In many cases, a user may exert force on an upper portion of theapparatus 100, for example, close to shoulder-height. Bycounterbalancing the weight as described above, the apparatus 100 may bemoved in a reasonably stable manner.

In the illustrated embodiment, the cart 130 includes the bottom shelf132 and an intermediate shelf 133, which are enclosed on three sides bywalls and on a fourth side by a door 135. The door 135 can be opened (asshown in FIG. 1) to provide access to the shelves 132, 133. In otherembodiments, the fourth side is not enclosed (e.g., the door 135 is notused). Many cart variations are possible. In some embodiments thebattery 134 can be placed on the bottom shelf 134 or the intermediateshelf 133.

FIG. 2 illustrates how various other devices can be supported on or nearthe apparatus 100 illustrated in FIG. 1. For example, the poles 110 ofthe stand 108 can be configured (e.g., of sufficient size and strength)to accommodate multiple devices 202, 204, 206. In some embodiments, oneor more COLLEAGUE® volumetric infusion pumps available from BaxterInternational Inc. of Deerfield, Ill. can be accommodated. In someembodiments, one or more Alaris® PC units available from CardinalHealth, Inc. of Dublin, Ohio can be accommodated. Furthermore, variousother medical devices (including the two examples mentioned here), canbe integrated with the disclosed monitoring device 102 such thatmultiple devices function in concert for the benefit of one or multiplepatients without the devices interfering with each other.

FIG. 3 illustrates the apparatus 100 of FIG. 1 as it can be connected toa patient 302. The monitoring device 102 can be used to determine theconcentration of one or more substances in a sample fluid. The samplefluid can come can come from the patient 302, as illustrated in FIG. 3,or the sample fluid can come from a fluid container, as illustrated inFIG. 3A. In some preferred embodiments, the sample fluid is whole blood.

In some embodiments (see, e.g., FIG. 3), the monitoring device 102 canalso deliver an infusion fluid to the patient 302. An infusion fluidcontainer 304 (e.g., a saline bag), which can contain infusion fluid(e.g., saline and/or medication), can be supported by the hook 112. Themonitoring device 102 can be in fluid communication with both thecontainer 304 and the sample fluid source (e.g., the patient 302),through tubes 306. The infusion fluid can comprise any combination offluids and/or chemicals. Some advantageous examples include (but are notlimited to): water, saline, dextrose, lactated Ringer's solution, drugs,and insulin.

The example monitoring device 102 schematically illustrated in FIG. 3allows the infusion fluid to pass to the patient 302 and/or uses theinfusion fluid itself (e.g., as a flushing fluid or a standard withknown optical properties, as discussed further below). In someembodiments, the monitoring device 102 may not employ infusion fluid.The monitoring device 102 may thus draw samples without delivering anyadditional fluid to the patient 302. The monitoring device 102 caninclude, but is not limited to, fluid handling and analysis apparatuses,connectors, passageways, catheters, tubing, fluid control elements,valves, pumps, fluid sensors, pressure sensors, temperature sensors,hematocrit sensors, hemoglobin sensors, calorimetric sensors, gas (e.g.,“bubble”) sensors, fluid conditioning elements, gas injectors, gasfilters, blood plasma separators, and/or communication devices (e.g.,wireless devices) to permit the transfer of information within themonitoring device 102 or between the monitoring device 102 and anetwork.

In some embodiments, the apparatus 100 is not connected to a patient andmay receive fluid samples from a container such as a decanter, flask,beaker, tube, cartridge, test strip, etc., or any other extracorporealfluid source. The container may include a biological fluid sample suchas, e.g., a body fluid sample. For example, FIG. 3A schematicallyillustrates an embodiment of the monitoring device 102 that isconfigured to receive a fluid sample from one or more test tubes 350.This embodiment of the monitoring device 102 is configured to perform invitro analysis of a fluid (or a fluid component) in the test tube 350.The test tube 350 may comprise a tube, vial, bottle, or other suitablecontainer or vessel. The test tube 350 may include an opening disposedat one end of the tube through which the fluid sample may be added priorto delivery of the test tube to the monitoring device 102. In someembodiments, the test tubes 350 may also include a cover adapted to sealthe opening of the tube. The cover may include an aperture configured topermit a tube, nozzle, needle, pipette, or syringe to dispense the fluidsample into the test tube 350. The test tubes 350 may comprise amaterial such as, for example, glass, polyethylene, or polymericcompounds. In various embodiments, the test tubes 350 may be re-usableunits or may be disposable, single-use units. In certain embodiments,the test tubes 350 may comprise commercially available lowpressure/vacuum sample bottles, test bottles, or test tubes.

In the embodiment shown in FIG. 3A, the monitoring device 102 comprisesa fluid delivery system 360 configured to receive a container (e.g., thetest tube 350) containing a fluid sample and deliver the fluid sample toa fluid handling system (such as, e.g., fluid handling system 404described below). In some embodiments, the fluid handling systemdelivers a portion of the fluid sample to an analyte detection systemfor in vitro measurement of one or more physiological parameters (e.g.,an analyte concentration). Prior to measurement, the fluid handlingsystem may, in some embodiments, separate the fluid sample intocomponents, and a measurement may be performed on one or more of thecomponents. For example, the fluid sample in the test tube 350 maycomprise whole blood, and the fluid handling system may separate bloodplasma from the sample (e.g., by filtering and/or centrifuging).

In the embodiment illustrated in FIG. 3A, the fluid delivery system 360comprises a carousel 362 having one or more openings 364 adapted toreceive the test tube 350. The carousel 362 may comprise one, two, four,six, twelve, or more openings 364. In the illustrated embodiment, thecarousel 362 is configured to rotate around a central axis or spindle366 so that a test tube 350 inserted into one of the openings 364 isdelivered to the monitoring device 102. In certain embodiments, thefluid handling system of the monitoring device 102 comprises a samplingprobe that is configured to collect a portion of the fluid sample fromthe test tube 350 (e.g., by suction or aspiration). The collectedportion may then be transported in the device 102 as further describedbelow (see, e.g., FIGS. 4-7). For example, in one embodiment suitablefor use with whole blood, the collected portion of the whole bloodsample is transported to a centrifuge for separation into blood plasma,a portion of the blood plasma is transported to an infrared spectroscopefor measurement of one or more analytes (e.g., glucose), and themeasured blood plasma is then transported to a waste container fordisposal.

In other embodiments of the apparatus 100 shown in FIG. 3A, the fluiddelivery system 360 may comprise a turntable, rack, or caddy adapted toreceive the test tube 350. In yet other embodiments, the monitoringdevice 102 may comprise an inlet port adapted to receive the test tube350. Additionally, in other embodiments, the fluid sample may bedelivered to the apparatus 100 using a test cartridge, a test strip, orother suitable container. Many variations are possible.

In some embodiments, one or more components of the apparatus 100 can belocated at another facility, room, or other suitable remote location.One or more components of the monitoring device 102 can communicate withone or more other components of the monitoring device 102 (or with otherdevices) by communication interface(s) such as, but not limited to,optical interfaces, electrical interfaces, and/or wireless interfaces.These interfaces can be part of a local network, internet, wirelessnetwork, or other suitable networks.

System Overview

FIG. 4 is a block diagram of a system 400 for sampling and analyzingfluid samples. The monitoring device 102 can comprise such a system. Thesystem 400 can include a fluid source 402 connected to a fluid-handlingsystem 404. The fluid-handling system 404 includes fluid passageways andother components that direct fluid samples. Samples can be withdrawnfrom the fluid source 402 and analyzed by an optical system 412. Thefluid-handling system 404 can be controlled by a fluid system controller405, and the optical system 412 can be controlled by an optical systemcontroller 413. The sampling and analysis system 400 can also include adisplay system 414 and an algorithm processor 416 that assist in fluidsample analysis and presentation of data.

In some embodiments, the sampling and analysis system 400 is a mobilepoint-of-care apparatus that monitors physiological parameters such as,for example, blood glucose concentration. Components within the system400 that may contact fluid and/or a patient, such as tubes andconnectors, can be coated with an antibacterial coating to reduce therisk of infection. Connectors between at least some components of thesystem 400 can include a self-sealing valve, such as a spring valve, inorder to reduce the risk of contact between port openings and fluids,and to guard against fluid escaping from the system. Other componentscan also be included in a system for sampling and analyzing fluid inaccordance with the described embodiments.

The sampling and analysis system 400 can include a fluid source 402 (ormore than one fluid source) that contain(s) fluid to be sampled. Thefluid-handling system 404 of the sampling and analysis system 400 isconnected to, and can draw fluid from, the fluid source 402. The fluidsource 402 can be, for example, a blood vessel such as a vein or anartery, a container such as a decanter, flask, beaker, tube, cartridge,test strip, etc., or any other corporeal or extracorporeal fluid source.For example, in some embodiments, the fluid source 402 may be a vein orartery in the patient 302 (see, e.g., FIG. 3). In other embodiments, thefluid source 402 may comprise an extracorporeal container 350 of fluiddelivered to the system 400 for analysis (see, e.g., FIG. 3B). The fluidto be sampled can be, for example, blood, plasma, interstitial fluid,lymphatic fluid, or another fluid. In some embodiments, more than onefluid source can be present, and more than one fluid and/or type offluid can be provided.

In some embodiments, the fluid-handling system 404 withdraws a sample offluid from the fluid source 402 for analysis, centrifuges at least aportion of the sample, and prepares at least a portion of the sample foranalysis by an optical sensor such as a spectrophotometer (which can bepart of an optical system 412, for example). These functions can becontrolled by a fluid system controller 405, which can also beintegrated into the fluid-handling system 404. The fluid systemcontroller 405 can also control the additional functions describedbelow.

In some embodiments, at least a portion of the sample is returned to thefluid source 402. At least some of the sample, such as portions of thesample that are mixed with other materials or portions that areotherwise altered during the sampling and analysis process, or portionsthat, for any reason, are not to be returned to the fluid source 402,can also be placed in a waste bladder (not shown in FIG. 4). The wastebladder can be integrated into the fluid-handling system 404 or suppliedby a user of the system 400. The fluid-handling system 404 can also beconnected to a saline source, a detergent source, and/or ananticoagulant source, each of which can be supplied by a user, attachedto the fluid-handling system 404 as additional fluid sources, and/orintegrated into the fluid-handling system 404.

Components of the fluid-handling system 404 can be modularized into oneor more non-disposable, disposable, and/or replaceable subsystems. Inthe embodiment shown in FIG. 4, components of the fluid-handling system404 are separated into a non-disposable subsystem 406, a firstdisposable subsystem 408, and a second disposable subsystem 410.

The non-disposable subsystem 406 can include components that, while theymay be replaceable or adjustable, do not generally require regularreplacement during the useful lifetime of the system 400. In someembodiments, the non-disposable subsystem 406 of the fluid-handlingsystem 404 includes one or more reusable valves and sensors. Forexample, the non-disposable subsystem 406 can include one or more valves(or non-disposable portions thereof), (e.g., pinch-valves, rotaryvalves, etc.), sensors (e.g., ultrasonic bubble sensors, non-contactpressure sensors, optical blood dilution sensors, etc). Thenon-disposable subsystem 406 can also include one or more pumps (ornon-disposable portions thereof). For example, some embodiments caninclude pumps available from Hospira. In some embodiments, thecomponents of the non-disposable subsystem 406 are not directly exposedto fluids and/or are not readily susceptible to contamination.

The first and second disposable subsystems 408, 410 can includecomponents that are regularly replaced under certain circumstances inorder to facilitate the operation of the system 400. For example, thefirst disposable subsystem 408 can be replaced after a certain period ofuse, such as a few days, has elapsed. Replacement may be necessary, forexample, when a bladder within the first disposable subsystem 408 isfilled to capacity. Such replacement may mitigate fluid systemperformance degradation associated with and/or contamination wear onsystem components.

In some embodiments, the first disposable subsystem 408 includescomponents that may contact fluids such as patient blood, saline,flushing solutions, anticoagulants, and/or detergent solutions. Forexample, the first disposable subsystem 408 can include one or moretubes, fittings, cleaner pouches and/or waste bladders. The componentsof the first disposable subsystem 408 can be sterilized in order todecrease the risk of infection and can be configured to be easilyreplaceable.

In some embodiments, the second disposable subsystem 410 can be designedto be replaced under certain circumstances. For example, the seconddisposable subsystem 410 can be replaced when the patient beingmonitored by the system 400 is changed. The components of the seconddisposable subsystem 410 may not need replacement at the same intervalsas the components of the first disposable subsystem 408. For example,the second disposable subsystem 410 can include a sample holder and/orat least some components of a centrifuge, components that may not becomefilled or quickly worn during operation of the system 400. Replacementof the second disposable subsystem 410 can decrease or eliminate therisk of transferring fluids from one patient to another during operationof the system 400, enhance the measurement performance of system 400,and/or reduce the risk of contamination or infection.

In some embodiments, the sample holder of the second disposablesubsystem 410 receives the sample obtained from the fluid source 402 viafluid passageways of the first disposable subsystem 408. The sampleholder is a container that can hold fluid for the centrifuge and caninclude a window to the sample for analysis by a spectrometer. In someembodiments, the sample holder includes windows that are made of amaterial that is substantially transparent to electromagnetic radiationin the mid-infrared range of the spectrum. For example, the sampleholder windows can be made of calcium fluoride.

An injector can provide a fluid connection between the first disposablesubsystem 408 and the sample holder of the second disposable subsystem410. In some embodiments, the injector can be removed from the sampleholder to allow for free spinning of the sample holder duringcentrifugation.

In some embodiments, the components of the sample are separated bycentrifuging for a period of time before measurements are performed bythe optical system 412. For example, a fluid sample (e.g., a bloodsample) can be centrifuged at a relatively high speed. The sample can bespun at a certain number of revolutions per minute (RPM) for a givenlength of time to separate blood plasma for spectral analysis. In someembodiments, the fluid sample is spun at about 7200 RPM. In someembodiments, the sample is spun at about 5000 RPM. In some embodiments,the fluid sample is spun at about 4500 RPM. In some embodiments, thefluid sample is spun at more than one rate for successive time periods.The length of time can be approximately 5 minutes. In some embodiments,the length of time is approximately 2 minutes. Separation of a sampleinto the components can permit measurement of solute (e.g., glucose)concentration in plasma, for example, without interference from otherblood components. This kind of post-separation measurement, (sometimesreferred to as a “direct measurement”) has advantages over a solutemeasurement taken from whole blood because the proportions of plasma toother components need not be known or estimated in order to infer plasmaglucose concentration. In some embodiments, the separated plasma can beanalyzed electrically using one or more electrodes instead of, or inaddition to, being analyzed optically. This analysis may occur withinthe same device, or within a different device. For example, in certainembodiments, an optical analysis device can separate blood intocomponents, analyze the components, and then allow the components to betransported to another analysis device that can further analyze thecomponents (e.g., using electrical and/or electrochemical measurements).

An anticoagulant, such as, for example, heparin can be added to thesample before centrifugation to prevent clotting. The fluid-handlingsystem 404 can be used with a variety of anticoagulants, includinganticoagulants supplied by a hospital or other user of the monitoringsystem 400. A detergent solution formed by mixing detergent powder froma pouch connected to the fluid-handling system 404 with saline can beused to periodically clean residual protein and other sample remnantsfrom one or more components of the fluid-handling system 404, such asthe sample holder. Sample fluid to which anticoagulant has been addedand used detergent solution can be transferred into the waste bladder.

The system 400 shown in FIG. 4 includes an optical system 412 that canmeasure optical properties (e.g., transmission) of a fluid sample (or aportion thereof). In some embodiments, the optical system 412 measurestransmission in the mid-infrared range of the spectrum. In someembodiments, the optical system 412 includes a spectrometer thatmeasures the transmission of broadband infrared light through a portionof a sample holder filled with fluid. The spectrometer need not comeinto direct contact with the sample. As used herein, the term “sampleholder” is a broad term that carries its ordinary meaning as an objectthat can provide a place for fluid. The fluid can enter the sampleholder by flowing.

In some embodiments, the optical system 412 includes a filter wheel thatcontains one or more filters. In some embodiments, more than ten filterscan be included, for example twelve or fifteen filters. In someembodiments, more than 20 filters (e.g., twenty-five filters) aremounted on the filter wheel. The optical system 412 includes a lightsource that passes light through a filter and the sample holder to adetector. In some embodiments, a stepper motor moves the filter wheel inorder to position a selected filter in the path of the light. An opticalencoder can also be used to finely position one or more filters. In someembodiments, one or more tunable filters may be used to filter lightinto multiple wavelengths. The one or more tunable filters may providethe multiple wavelengths of light at the same time or at different times(e.g., sequentially). The light source included in the optical system412 may emit radiation in the ultraviolet, visible, near-infrared,mid-infrared, and/or far-infrared regions of the electromagneticspectrum. In some embodiments, the light source can be a broadbandsource that emits radiation in a broad spectral region (e.g., from about1500 nm to about 6000 nm). In other embodiments, the light source mayemit radiation at certain specific wavelengths. The light source maycomprise one or more light emitting diodes (LEDs) emitting radiation atone or more wavelengths in the radiation regions described herein. Inother embodiments, the light source may comprise one or more lasermodules emitting radiation at one or more wavelengths. The laser modulesmay comprise a solid state laser (e.g., a Nd:YAG laser), a semiconductorbased laser (e.g., a GaAs and/or InGaAsP laser), and/or a gas laser(e.g., an Ar-ion laser). In some embodiments, the laser modules maycomprise a fiber laser. The laser modules may emit radiation at certainfixed wavelengths. In some embodiments, the emission wavelength of thelaser module(s) may be tunable over a wide spectral range (e.g., about30 nm to about 100 nm). In some embodiments, the light source includedin the optical system 412 may be a thermal infrared emitter. The lightsource can comprise a resistive heating element, which, in someembodiments, may be integrated on a thin dielectric membrane on amicromachined silicon structure. In one embodiment the light source isgenerally similar to the electrical modulated thermal infrared radiationsource, IRSource™, available from the Axetris Microsystems division ofLeister Technologies, LLC (Itasca, Ill.).

The optical system 412 can be controlled by an optical system controller413. The optical system controller can, in some embodiments, beintegrated into the optical system 412. In some embodiments, the fluidsystem controller 405 and the optical system controller 413 cancommunicate with each other as indicated by the line 411. In someembodiments, the function of these two controllers can be integrated anda single controller can control both the fluid-handling system 404 andthe optical system 412. Such an integrated control can be advantageousbecause the two systems are preferably integrated, and the opticalsystem 412 is preferably configured to analyze the very same fluidhandled by the fluid-handling system 404. Indeed, portions of thefluid-handling system 404 (e.g., the sample holder described above withrespect to the second disposable subsystem 410 and/or at least somecomponents of a centrifuge) can also be components of the optical system412. Accordingly, the fluid-handling system 404 can be controlled toobtain a fluid sample for analysis by optical system 412, when the fluidsample arrives, the optical system 412 can be controlled to analyze thesample, and when the analysis is complete (or before), thefluid-handling system 404 can be controlled to return some of the sampleto the fluid source 402 and/or discard some of the sample, asappropriate.

The system 400 shown in FIG. 4 includes a display system 414 thatprovides for communication of information to a user of the system 400.In some embodiments, the display 414 can be replaced by or supplementedwith other communication devices that communicate in non-visual ways.The display system 414 can include a display processor that controls orproduces an interface to communicate information to the user. Thedisplay system 414 can include a display screen. One or more parameterssuch as, for example, blood glucose concentration, system 400 operatingparameters, and/or other operating parameters can be displayed on amonitor (not shown) associated with the system 400. An example of oneway such information can be displayed is shown in FIGS. 24 and 25. Insome embodiments, the display system 414 can communicate measuredphysiological parameters and/or operating parameters to a computersystem over a communications connection.

The system 400 shown in FIG. 4 includes an algorithm processor 416 thatcan receive spectral information, such as optical density (OD) values(or other analog or digital optical data) from the optical system 412and or the optical system controller 413. In some embodiments, thealgorithm processor 416 calculates one or more physiological parametersand can analyze the spectral information. Thus, for example and withoutlimitation, a model can be used that determines, based on the spectralinformation, physiological parameters of fluid from the fluid source402. The algorithm processor 416, a controller that may be part of thedisplay system 414, and any embedded controllers within the system 400can be connected to one another with a communications bus.

Some embodiments of the systems described herein (e.g., the system 400),as well as some embodiments of each method described herein, can includea computer program accessible to and/or executable by a processingsystem, e.g., a one or more processors and memories that are part of anembedded system. Indeed, the controllers may comprise one or morecomputers and/or may use software. Thus, as will be appreciated by thoseskilled in the art, various embodiments may be embodied as a method, anapparatus such as a special purpose apparatus, an apparatus such as adata processing system, or a carrier medium, e.g., a computer programproduct. The carrier medium carries one or more computer readable codesegments for controlling a processing system to implement a method.Accordingly, various embodiments may take the form of a method, anentirely hardware embodiment, an entirely software embodiment or anembodiment combining software and hardware aspects. Furthermore, any oneor more of the disclosed methods (including but not limited to thedisclosed methods of measurement analysis, interferent determination,and/or calibration constant generation) may be stored as one or morecomputer readable code segments or data compilations on a carriermedium. Any suitable computer readable carrier medium may be usedincluding a magnetic storage device such as a diskette or a hard disk; amemory cartridge, module, card or chip (either alone or installed withina larger device); or an optical storage device such as a CD or DVD.

Fluid Handling System

The generalized fluid-handling system 404 can have variousconfigurations. In this context, FIG. 5 schematically illustrates thelayout of an example embodiment of a fluid system 510. In this schematicrepresentation, various components are depicted that may be part of anon-disposable subsystem 406, a first disposable subsystem 408, a seconddisposable subsystem 410, and/or an optical system 412. The fluid system510 is described practically to show an example cycle as fluid is drawnand analyzed.

In addition to the reference numerals used below, the various portionsof the illustrated fluid system 510 are labeled for convenience withletters to suggest their roles as follows: T# indicates a section oftubing. C# indicates a connector that joins multiple tubing sections. V#indicates a valve. BS# indicates a bubble sensor or ultrasonic airdetector. N# indicates a needle (e.g., a needle that injects sample intoa sample holder). PS# indicates a pressure sensor (e.g., a reusablepressure sensor). Pump# indicates a fluid pump (e.g., a syringe pumpwith a disposable body and reusable drive). “Hb 12” indicates a sensorfor hemoglobin (e.g., a dilution sensor that can detect hemoglobinoptically).

The term “valve” as used herein is a broad term and is used, inaccordance with its ordinary meaning, to refer to any flow regulatingdevice. For example, the term “valve” can include, without limitation,any device or system that can controllably allow, prevent, or inhibitthe flow of fluid through a fluid passageway. The term “valve” caninclude some or all of the following, alone or in combination: pinchvalves, rotary valves, stop cocks, pressure valves, shuttle valves,mechanical valves, electrical valves, electromechanical flow regulators,etc. In some embodiments, a valve can regulate flow using gravitationalmethods or by applying electrical voltages or by both.

The term “pump” as used herein is a broad term and is used, inaccordance with its ordinary meaning, to refer to any device that canurge fluid flow. For example, the term “pump” can include anycombination of the following: syringe pumps, peristaltic pumps, vacuumpumps, electrical pumps, mechanical pumps, hydraulic pumps, etc. Pumpsand/or pump components that are suitable for use with some embodimentscan be obtained, for example, from or through Hospira.

The function of the valves, pumps, actuators, drivers, motors (e.g., thecentrifuge motor), etc. described below is controlled by one or morecontrollers (e.g., the fluid system controller 405, the optical systemcontroller 413, etc.) The controllers can include software, computermemory, electrical and mechanical connections to the controlledcomponents, etc.

At the start of a measurement cycle, most lines, including a patienttube 512 (T1), an Arrival sensor tube 528 (T4), an anticoagulant valvetube 534 (T3), and a sample cell 548 can be filled with saline that canbe introduced into the system through the infusion tube 514 and thesaline tube 516, and which can come from an infusion pump 518 and/or asaline bag 520. The infusion pump 518 and the saline bag 520 can beprovided separately from the system 510. For example, a hospital can useexisting saline bags and infusion pumps to interface with the describedsystem. The infusion valve 521 can be open to allow saline to flow intothe tube 512 (T1).

Before drawing a sample, the saline in part of the system 510 can bereplaced with air. Thus, for example, the following valves can beclosed: air valve 503 (PV0), the detergent tank valve 559 (V7 b), 566(V3 b), 523 (V0), 529 (V7 a), and 563 (V2 b). At the same time, thefollowing valves can be open: valves 531 (V1 a), 533 (V3 a) and 577 (V4a). Simultaneously, a second pump 532 (pump #0) pumps air through thesystem 510 (including tube 534 (T3), sample cell 548, and tube 556(T6)), pushing saline through tube 534 (T3) and sample cell 548 into awaste bladder 554.

Next, a sample can be drawn. With the valves 542 (PV1), 559 (V7 b), and561 (V4 b) closed, a first pump 522 (pump #1) is actuated to draw samplefluid to be analyzed (e.g. blood) from a fluid source (e.g., alaboratory sample container, a living patient, etc.) up into the patienttube 512 (T1), through the tube past the two flanking portions of theopen pinch-valve 523 (V0), through the first connector 524 (C1), intothe looped tube 530, past the arrival sensor 526 (Hb12), and into thearrival sensor tube 528 (T4). The arrival sensor 526 may be used todetect the presence of blood in the tube 528 (T4). For example in someembodiments, the arrival sensor 526 may comprise a hemoglobin sensor. Insome other embodiments, the arrival sensor 526 may comprise a colorsensor that detects the color of fluid flowing through the tube 528(T4). During this process, the valve 529 (V7 a) and 523 (V0) are open tofluid flow, and the valves 531 (V1 a), 533 (V3 a), 542 (PV1), 559 (V7b), and 561 (V4 b) can be closed and therefore block (or substantiallyblock) fluid flow by pinching the tube.

Before drawing the sample, the tubes 512 (T1) and 528 (T4) are filledwith saline and the hemoglobin (Hb) level is zero. The tubes that arefilled with saline are in fluid communication with the sample source(e.g., the fluid source 402). The sample source can be the vessels of aliving human or a pool of liquid in a laboratory sample container, forexample. When the saline is drawn toward the first pump 522, fluid to beanalyzed is also drawn into the system because of the suction forces inthe closed fluid system. Thus, the first pump 522 draws a relativelycontinuous column of fluid that first comprises generally nondilutedsaline, then a mixture of saline and sample fluid (e.g., blood), andthen eventually nondiluted sample fluid. In the example illustratedhere, the sample fluid is blood.

The arrival sensor 526 (Hb12) can detect and/or verify the presence ofblood in the tubes. For example, in some embodiments, the arrival sensor526 can determine the color of the fluid in the tubes. In someembodiments, the arrival sensor 526 (Hb12) can detect the level ofHemoglobin in the sample fluid. As blood starts to arrive at the arrivalsensor 526 (Hb12), the sensed hemoglobin level rises. A hemoglobin levelcan be selected, and the system can be pre-set to determine when thatlevel is reached. A controller such as the fluid system controller 405of FIG. 4 can be used to set and react to the pre-set value, forexample. In some embodiments, when the sensed hemoglobin level reachesthe pre-set value, substantially undiluted sample is present at thefirst connector 524 (C1). The preset value can depend, in part, on thelength and diameter of any tubes and/or passages traversed by thesample. In some embodiments, the pre-set value can be reached afterapproximately 2 mL of fluid (e.g., blood) has been drawn from a fluidsource. A nondiluted sample can be, for example, a blood sample that isnot diluted with saline solution, but instead has the characteristics ofthe rest of the blood flowing through a patient's body. A loop of tubing530 (e.g., a 1-mL loop) can be advantageously positioned as illustratedto help insure that undiluted fluid (e.g., undiluted blood) is presentat the first connector 524 (C1) when the arrival sensor 526 registersthat the preset Hb threshold is crossed. The loop of tubing 530 providesadditional length to the Arrival sensor tube 528 (T4) to make it lesslikely that the portion of the fluid column in the tubing at the firstconnector 524 (C1) has advanced all the way past the mixture of salineand sample fluid, and the nondiluted blood portion of that fluid hasreached the first connector 524 (C1).

In some embodiments, when nondiluted blood is present at the firstconnector 524 (C1), a sample is mixed with an anticoagulant and isdirected toward the sample cell 548. An amount of anticoagulant (e.g.,heparin) can be introduced into the tube 534 (T3), and then theundiluted blood is mixed with the anticoagulant. A heparin vial 538(e.g., an insertable vial provided independently by the user of thesystem 510) can be connected to a tube 540. An anticoagulant valve 541(which can be a shuttle valve, for example) can be configured to connectto both the tube 540 and the anticoagulant valve tube 534 (T3). Thevalve can open the tube 540 to a suction force (e.g., created by thepump 532), allowing heparin to be drawn from the vial 538 into the valve541. Then, the anticoagulant valve 541 can slide the heparin over intofluid communication with the anticoagulant valve tube 534 (T3). Theanticoagulant valve 541 can then return to its previous position. Thus,heparin can be shuttled from the tube 540 into the anticoagulant valvetube 534 (T3) to provide a controlled amount of heparin into the tube534 (T3).

With the valves 542 (PV1), 559 (V7 b), 561 (V4 b), 523 (V0), 531 (V1 a),566 (V3 b), and 563 (V2 b) closed, and the valves 529 (V7 a) and 553 (V3a) open, first pump 522 (pump #1) pushes the sample from tube 528 (T4)into tube 534 (T3), where the sample mixes with the heparin injected bythe anticoagulant valve 541 as it flows through the system 510. As thesample proceeds through the tube 534 (T3), the air that was previouslyintroduced into the tube 534 (T3) is displaced. The sample continues toflow until a bubble sensor 535 (BS9) indicates a change from air to aliquid, and thus the arrival of a sample at the bubble sensor. In someembodiments, the volume of tube 534 (T3) from connector 524 (C1) tobubble sensor 535 (BS9) is a known and/or engineered amount, and may beapproximately 500 μL, 200 μL or 100 μL, for example.

When bubble sensor 535 (BS9) indicates the presence of a sample, theremainder of the sampled blood can be returned to its source (e.g., thepatient veins or arteries). The first pump 522 (pump #1) pushes theblood out of the Arrival sensor tube 528 (T4) and back to the patient byopening the valve 523 (V0), closing the valves 531 (V1 a) and 533 (V3a), and keeping the valve 529 (V7 a) open. The Arrival sensor tube 528(T4) is preferably flushed with approximately 2 mL of saline. This canbe accomplished by closing the valve 529 (V7 a), opening the valve 542(PV1), drawing saline from the saline source 520 into the tube 544,closing the valve 542 (PV1), opening the valve 529 (V7 a), and forcingthe saline down the Arrival sensor tube 528 (T4) with the pump 522. Insome embodiments, less than two minutes elapse between the time thatblood is drawn from the patient and the time that the blood is returnedto the patient.

Following return of the unused patient blood sample, the sample ispushed up the anticoagulant valve tube 534 (T3), through the secondconnector 546 (C2), and into the sample cell 548, which can be locatedon the centrifuge rotor 550. This fluid movement is facilitated by thecoordinated action (either pushing or drawing fluid) of the pump 522(pump #1), the pump 532 (pump #0), and the various illustrated valves.In particular, valve 531 (V1 a) can be opened, and valves 503 (PV0) and559 (V7 b) can be closed. Pump movement and valve position correspondingto each stage of fluid movement can be coordinated by one ore multiplecontrollers, such as the fluid system controller 405 of FIG. 4.

After the unused sample is returned to the patient, the sample can bedivided into separate slugs before being delivered into the sample cell548. Thus, for example, valve 553 (V3 a) is opened, valves 566 (V3 b),523 (V0) and 529 (V7 a) are closed, and the pump 532 (pump #0) uses airto push the sample toward sample cell 548. In some embodiments, thesample (for example, 200 μL or 100 μL) is divided into multiple (e.g.,more than two, five, or four) “slugs” of sample, each separated by asmall amount of air. As used herein, the term “slug” refers to acontinuous column of fluid that can be relatively short. Slugs can beseparated from one another by small amounts of air (or bubbles) that canbe present at intervals in the tube. In some embodiments, the slugs areformed by injecting or drawing air into fluid in the first connector 546(C2).

In some embodiments, when the leading edge of the sample reaches bloodsensor 553 (BS14), a small amount of air (the first “bubble”) isinjected at a connector C6. This bubble helps define the first “slug” ofliquid, which extends from the bubble sensor to the first bubble. Insome embodiments, the valves 533 (V3 a) and 556 (V3 b) are alternatelyopened and closed to form a bubble at connector C6, and the sample ispushed toward the sample cell 548. Thus, for example, with pump 532actuated, valve 566 V(3 b) is briefly opened and valve 533 (V3 a) isbriefly closed to inject a first air bubble into the sample.

In some embodiments, the volume of the tube 534 (T3) from the connector546 (C2) to the bubble sensor 552 (BS14) is less than the volume of tube534 (T3) from the connector 524 (C1) to the bubble sensor 535 (BS9).Thus, for example and without limitation, the volume of the tube 534(T3) from the connector 524 (C1) to the bubble sensor 535 (BS9) can bein the range of approximately 80 μL to approximately 120 μL, (e.g., 100μL,) and the volume of the tube 534 (T3) from the connector 546 (C2) tothe bubble sensor 552 (BS14) can be in the range of approximately 5 μLto approximately 25 μL (e.g., 15 μL). In some embodiments, multipleblood slugs are created. For example, more than two blood slugs can becreated, each having a different volume. In some embodiments, five bloodslugs are created, each having approximately the same volume ofapproximately 20 μL each. In some embodiments, three blood slugs arecreated, the first two having a volume of 10 μL and the last having avolume of 20 μL. In some embodiments, four blood slugs are created; thefirst three blood slugs can have a volume of approximately 15 μL and thefourth can have a volume of approximately 35 μL.

A second slug can be prepared by opening the valve 553 (V3 a), closingthe valve 566 (V3 b), with pump 532 (pump #0) operating to push thefirst slug through a first sample cell holder interface tube 582 (N1),through the sample cell 548, through a second sample cell holderinterface tube 584 (N2), and toward the waste bladder 554. When thefirst bubble reaches the bubble sensor 552 (BS 14), the open/closedconfigurations of valves 553 (V3 a) and 566 (V3 b) are reversed, and asecond bubble is injected into the sample, as before. A third slug canbe prepared in the same manner as the second (pushing the second bubbleto bubble sensor 552 (BS 14) and injecting a third bubble). After theinjection of the third air bubble, the sample can be pushed throughsystem 510 until the end of the sample is detected by bubble sensor 552(BS 14). The system can be designed such that when the end of the samplereaches this point, the last portion of the sample (a fourth slug) iswithin the sample cell 548, and the pump 532 can stop forcing the fluidcolumn through the anticoagulant valve tube 534 (T3) so that the fourthslug remains within the sample cell 548. Thus, the first three bloodslugs can serve to flush any residual saline out the sample cell 548.The three leading slugs can be deposited in the waste bladder 554 bypassing through the tube 556 (T6) and past the tube-flanking portions ofthe open pinch valve 557 (V4 a).

In some embodiments, the fourth blood slug is centrifuged for a givenlength of time (e.g., more than 1 minute, five minutes, or 2 minutes, totake three advantageous examples) at a relatively fast speed (e.g., 7200RPM, 5000 RPM, or 4500 RPM, to take three examples). Thus, for example,the sample cell holder interface tubes 582 (N1) and 584 (N2) disconnectthe sample cell 548 from the tubes 534 (T3) and 562 (T7), permitting thecentrifuge rotor 550 and the sample cell 548 to spin together. Spinningseparates a sample (e.g., blood) into its components, isolates theplasma, and positions the plasma in the sample cell 548 for measurement.The centrifuge 550 can be stopped with the sample cell 548 in a beam ofradiation (not shown) for analysis. The radiation, a detector, and logiccan be used to analyze a portion of the sample (e.g., the plasma)spectroscopically (e.g., for glucose, lactate, or other analyteconcentration). In some embodiments, some or all of the separatedcomponents (e.g., the isolated plasma) may be transported to a differentanalysis chamber. For example, another analysis chamber can have one ormore electrodes in electrical communication with the chamber's contents,and the separated components may be analyzed electrically. At anysuitable point, one or more of the separated components can betransported to the waste bladder 554 when no longer needed. In somechemical analysis systems and apparatus, the separated components areanalyzed electrically. Analysis devices may be connected serially, forexample, so that the analyzed substance from an optical analysis system(e.g., an “OptiScanner®” fluid analyzer) can be transferred to anindependent analysis device (e.g., a chemical analysis device) forsubsequent analysis. In certain embodiments, the analysis devices areintegrated into a single system. Many variations are possible.

In some embodiments, portions of the system 510 that contain blood afterthe sample cell 548 has been provided with a sample are cleaned toprevent blood from clotting. Accordingly, the centrifuge rotor 550 caninclude two passageways for fluid that may be connected to the samplecell holder interface tubes 582 (N1) and 584 (N2). One passageway issample cell 548, and a second passageway is a shunt 586. An embodimentof the shunt 586 is illustrated in more detail in FIG. 16 (see referencenumeral 1586).

The shunt 586 can allow cleaner (e.g., a detergent such as tergazyme A)to flow through and clean the sample cell holder interface tubes withoutflowing through the sample cell 548. After the sample cell 548 isprovided with a sample, the interface tubes 582 (N1) and 584 (N2) aredisconnected from the sample cell 548, the centrifuge rotor 550 isrotated to align the shunt 586 with the interface tubes 582 (N1) and 584(N2), and the interface tubes are connected with the shunt. With theshunt in place, the detergent tank 559 is pressurized by the second pump532 (pump #0) with valves 561 (V4 b) and 563 (V2 b) open and valves 557(V4 a) and 533 (V3 a) closed to flush the cleaning solution back throughthe interface tubes 582 (N1) and 584 (N2) and into the waste bladder554. Subsequently, saline can be drawn from the saline bag 520 for asaline flush. This flush pushes saline through the Arrival sensor tube528 (T4), the anticoagulant valve tube 534 (T3), the sample cell 548,and the waste tube 556 (T6). Thus, in some embodiments, the followingvalves are open for this flush: 529 (V7 a), 533 (V3 a), 557 (V4 a), andthe following valves are closed: 542 (PV1), 523 (V0), 531 (V1 a), 566(V3 b), 563 (V2 b), and 561 (V4 b).

Following analysis, the second pump 532 (pump #0) flushes the samplecell 548 and sends the flushed contents to the waste bladder 554. Thisflush can be done with a cleaning solution from the detergent tank 558.In some embodiments, the detergent tank valve 559 (V7 b) is open,providing fluid communication between the second pump 532 and thedetergent tank 558. The second pump 532 forces cleaning solution fromthe detergent tank 558 between the tube-flanking portions of the openpinch valve 561 and through the tube 562 (T7). The cleaning flush canpass through the sample cell 548, through the second connector 546,through the tube 564 (T5) and the open valve 563 (V2 b), and into thewaste bladder 554.

Subsequently, the first pump 522 (pump #1) can flush the cleaningsolution out of the sample cell 548 using saline in drawn from thesaline bag 520. This flush pushes saline through the Arrival sensor tube528 (T4), the anticoagulant valve tube 534 (T3), the sample cell 548,and the waste tube 556 (T6). Thus, in some embodiments, the followingvalves are open for this flush: 529 (V7 a), 533 (V3 a), 557 (V4 a), andthe following valves are closed: 542 (PV1), 523 (V0), 531 (V1 a), 566(V3 b), 563 (V2 b), and 561 (V4 b).

When the fluid source is a living entity such as a patient, a low flowof saline (e.g., 1-5 mL/hr) is preferably moved through the patient tube512 (T1) and into the patient to keep the patient's vessel open (e.g.,to establish a keep vessel open, or “KVO” flow). This KVO flow can betemporarily interrupted when fluid is drawn into the fluid system 510.The source of this KVO flow can be the infusion pump 518, the third pump568 (pump #3), or the first pump 522 (pump #1). In some embodiments, theinfusion pump 518 can run continuously throughout the measurement cycledescribed above. This continuous flow can advantageously avoid anyalarms that may be triggered if the infusion pump 518 senses that theflow has stopped or changed in some other way. In some embodiments, whenthe infusion valve 521 closes to allow pump 522 (pump #1) to withdrawfluid from a fluid source (e.g., a patient), the third pump 568 (pump#3) can withdraw fluid through the connector 570, thus allowing theinfusion pump 518 to continue pumping normally as if the fluid path wasnot blocked by the infusion valve 521. If the measurement cycle is abouttwo minutes long, this withdrawal by the third pump 568 can continue forapproximately two minutes. Once the infusion valve 521 is open again,the third pump 568 (pump #3) can reverse and insert the saline back intothe system at a low flow rate. Preferably, the time between measurementcycles is longer than the measurement cycle itself (for example, thetime interval can be longer than ten minutes, shorter than ten minutes,shorter than five minutes, longer than two minutes, longer than oneminute, etc.). Accordingly, the third pump 568 can insert fluid backinto the system at a lower rate than it withdrew that fluid. This canhelp prevent an alarm by the infusion pump.

FIG. 6 schematically illustrates another embodiment of a fluid systemthat can be part of a system for withdrawing and analyzing fluidsamples. In this embodiment, the anticoagulant valve 541 has beenreplaced with a syringe-style pump 588 (Pump Heparin) and a series ofpinch valves around a junction between tubes. For example, a heparinpinch valve 589 (Vhep) can be closed to prevent flow from or to the pump588, and a heparin waste pinch valve 590 can be closed to prevent flowfrom or to the waste container from this junction through the heparinwaste tube 591. This embodiment also illustrates the shunt 592schematically. Other differences from FIG. 5 include the check valve 593located near the detergent tank 558 and the patient loop 594. Thereference letters D, for example, the one indicated at 595, refer tocomponents that are advantageously located on the door. The referenceletters M, for example, the one indicated at 596, refer to componentsthat are advantageously located on the monitor. The reference letters B,for example, the one indicated at 597, refer to components that can beadvantageously located on both the door and the monitor.

In some embodiments, the system 400 (see FIG. 4), the apparatus 100 (seeFIG. 1), or even the monitoring device 102 (see FIG. 1) itself can alsoactively function not only to monitor analyte levels (e.g., glucose),but also to change and/or control analyte levels. Thus, the monitoringdevice 102 can be both a monitoring and an infusing device. In someembodiments, the fluid handling system 510 can include an optionalanalyte control subsystem 2780 that will be further described below (seediscussion of analyte control).

In certain embodiments, analyte levels in a patient can be adjusteddirectly (e.g., by infusing or extracting glucose) or indirectly (e.g.,by infusing or extracting insulin). FIG. 6 illustrates one way ofproviding this function. The infusion pinch valve 598 (V8) can allow theport sharing pump 599 (compare to the third pump 568 (pump #3) in FIG.5) to serve two roles. In the first role, it can serve as a “portsharing” pump. The port sharing function is described with respect tothe third pump 568 (pump #3) of FIG. 5, where the third pump 568 (pump#3) can withdraw fluid through the connector 570, thus allowing theinfusion pump 518 to continue pumping normally as if the fluid path wasnot blocked by the infusion valve 521. In the second role, the portsharing pump 599 can serve as an infusion pump. The infusion pump roleallows the port sharing pump 599 to draw a substance (e.g., glucose,saline, etc.) from another source when the infusion pinch valve 598 isopen, and then to infuse that substance into the system or the patientwhen the infusion pinch valve 598 is closed. This can occur, forexample, in order to change the level of a substance in a patient inresponse to a reading by the monitor that the substance is too low. Insome embodiments, one or more of the pumps may comprise a reversibleinfusion pump configured to interrupt the flow of the infusion fluid anddraw a sample of blood for analysis.

Mechanical/Fluid System Interface

FIG. 7 is an oblique schematic depiction of a modular monitoring device700, which can correspond to the monitoring device 102. The modularmonitoring device 700 includes a body portion 702 having a receptacle704, which can be accessed by moving a movable portion 706. Thereceptacle 704 can include connectors (e.g., rails, slots, protrusions,resting surfaces, etc.) with which a removable portion 710 caninterface. In some embodiments, portions of a fluidic system thatdirectly contact fluid are incorporated into one or more removableportions (e.g., one or more disposable cassettes, sample holders, tubingcards, etc.). For example, a removable portion 710 can house at least aportion of the fluid system 510 described previously, including portionsthat contact sample fluids, saline, detergent solution, and/oranticoagulant.

In some embodiments, a non-disposable fluid-handling subsystem 708 isdisposed within the body portion 702 of the monitoring device 700. Thefirst removable portion 710 can include one or more openings that allowportions of the non-disposable fluid-handling subsystem 708 to interfacewith the removable portion 710. For example, the non-disposablefluid-handling subsystem 708 can include one or more pinch valves thatare designed to extend through such openings to engage one or moresections of tubing. When the first removable portion 710 is present in acorresponding first receptacle 704, actuation of the pinch valves canselectively close sections of tubing within the removable portion. Thenon-disposable fluid-handling subsystem 708 can also include one or moresensors that interface with connectors, tubing sections, or pumpslocated within the first removable portion 710. The non-disposablefluid-handling subsystem 708 can also include one or more actuators(e.g., motors) that can actuate moveable portions (e.g., the plunger ofa syringe) that may be located in the removable portion F10. A portionof the non-disposable fluid-handling subsystem 708 can be located on orin the moveable portion F06 (which can be a door having a slide or ahinge, a detachable face portion, etc.).

In the embodiment shown in FIG. 7, the monitoring device 700 includes anoptical system 714 disposed within the body portion 702. The opticalsystem 714 can include a light source and a detector that are adapted toperform measurements on fluids within a sample holder (not shown). Thelight source may comprise a fixed wavelength light source and/or atunable light source. The light source may comprise one or more sourcesincluding, for example, broadband sources, LEDs, and lasers. In someembodiments, the sample holder comprises a removable portion, which canbe associated with or disassociated from the removable portion F10. Thesample holder can include an optical window through which the opticalsystem 714 can emit radiation for measuring properties of a fluid in thesample holder. The optical system 714 can include other components suchas, for example, a power supply, a centrifuge motor, a filter wheel,and/or a beam splitter.

In some embodiments, the removable portion 710 and the sample holder areadapted to be in fluid communication with each other. For example, theremovable portion 710 can include a retractable injector that injectsfluids into a sample holder. In some embodiments, the sample holder cancomprise or be disposed in a second removable portion (not shown). Insome embodiments, the injector can be retracted to allow the centrifugeto rotate the sample holder freely.

The body portion 702 of the monitoring device 700 can also include oneor more connectors for an external battery (not shown). The externalbattery can serve as a backup emergency power source in the event that aprimary emergency power source such as, for example, an internal battery(not shown) is exhausted.

FIG. 7 shows an embodiment of a system having subcomponents illustratedschematically. By way of a more detailed (but nevertheless non-limiting)example, FIG. 8 and FIG. 9 show more details of the shape and physicalconfiguration of a sample embodiment.

FIG. 8 shows a cut-away side view of a monitoring device 800 (which cancorrespond, for example, to the device 102 shown in FIG. 1). The device800 includes a casing 802. The monitoring device 800 can have a fluidsystem. For example, the fluid system can have subsystems, and a portionor portions thereof can be disposable, as schematically depicted in FIG.4. As depicted in FIG. 8, the fluid system is generally located at theleft-hand portion of the casing 802, as indicated by the reference 801.The monitoring device 800 can also have an optical system. In theillustrated embodiment, the optical system is generally located in theupper portion of the casing 802, as indicated by the reference 803.Advantageously, however, the fluid system 801 and the optical system 803can both be integrated together such that fluid flows generally througha portion of the optical system 803, and such that radiation flowsgenerally through a portion of the fluid system 801.

Depicted in FIG. 8 are examples of ways in which components of thedevice 800 mounted within the casing 802 can interface with componentsof the device 800 that comprise disposable portions. Not all componentsof the device 800 are shown in FIG. 8. A disposable portion 804 having avariety of components is shown in the casing 802. In some embodiments,one or more actuators 808 housed within the casing 802, operate syringebodies 810 located within a disposable portion 804. The syringe bodies810 are connected to sections of tubing 816 that move fluid amongvarious components of the system. The movement of fluid is at leastpartially controlled by the action of one or more pinch valves 812positioned within the casing 802. The pinch valves 812 have arms 814that extend within the disposable portion 804. Movement of the arms 814can constrict a section of tubing 816.

In some embodiments, a sample cell holder 820 can engage a centrifugemotor 818 mounted within the casing 802 of the device 800. A filterwheel motor 822 disposed within the housing 802 rotates a filter wheel824, and in some embodiments, aligns one or more filters with an opticalpath. An optical path can originate at a source 826 within the housing802 that can be configured to emit a beam of radiation (e.g., infraredradiation, visible radiation, ultraviolet radiation, etc.) through thefilter and the sample cell holder 820 and to a detector 828. A detector828 can measure the optical density of the light when it reaches thedetector.

FIG. 9 shows a cut-away perspective view of an alternative embodiment ofa monitoring device 900. Many features similar to those illustrated inFIG. 8 are depicted in this illustration of an alternative embodiment. Afluid system 901 can be partially seen. The disposable portion 904 isshown in an operative position within the device. One of the actuators808 can be seen next to a syringe body 910 that is located within thedisposable portion 904. Some pinch valves 912 are shown next to afluid-handling portion of the disposable portion 904. In this figure, anoptical system 903 can also be partially seen. The sample holder 920 islocated underneath the centrifuge motor 918. The filter wheel motor 922is positioned near the radiation source 926, and the detector 928 isalso illustrated.

FIG. 10 illustrates two views of a cartridge 1000 that can interfacewith a fluid system such as the fluid system 510 of FIG. 5. Thecartridge 1000 can be configured for insertion into a receptacle of thedevice 800 of FIG. 8 and/or the device 900 shown in FIG. 9. In someembodiments, the cartridge 1000 can comprise a portion that isdisposable and a portion that is reusable. In some embodiments, thecartridge 1000 can be disposable. The cartridge 1000 can fill the roleof the removable portion 710 of FIG. 7, for example. In someembodiments, the cartridge 1000 can be used for a system having only onedisposable subsystem, making it a simple matter for a health careprovider to replace and/or track usage time of the disposable portion.In some embodiments, the cartridge 1000 includes one or more featuresthat facilitate insertion of the cartridge 1000 into a correspondingreceptacle. For example, the cartridge 1000 can be shaped so as topromote insertion of the cartridge 1000 in the correct orientation. Thecartridge 1000 can also include labeling or coloring affixed to orintegrated with the cartridge's exterior casing that help a handlerinsert the cartridge 1000 into a receptacle properly.

The cartridge 1000 can include one or more ports for connecting tomaterial sources or receptacles. Such ports can be provided to connectto, for example, a saline source, an infusion pump, a sample source,and/or a source of gas (e.g., air, nitrogen, etc.). The ports can beconnected to sections of tubing within the cartridge 1000. In someembodiments, the sections of tubing are opaque or covered so that fluidswithin the tubing cannot be seen, and in some embodiments, sections oftubing are transparent to allow interior contents (e.g., fluid) to beseen from outside.

The cartridge 1000 shown in FIG. 10 can include a sample injector 1006.The sample injector 1006 can be configured to inject at least a portionof a sample into a sample holder (see, e.g., the sample cell 548), whichcan also be incorporated into the cartridge 1000. The sample injector1006 can include, for example, the sample cell holder interface tubes582 (N1) and 584 (N2) of FIG. 5, embodiments of which are alsoillustrated in FIG. 15.

The housing of the cartridge 1000 can include a tubing portion 1008containing within it a card having one or more sections of tubing. Insome embodiments, the body of the cartridge 1000 includes one or moreapertures 1009 through which various components, such as, for example,pinch valves and sensors, can interface with the fluid-handling portioncontained in the cartridge 1000. The sections of tubing found in thetubing portion 1008 can be aligned with the apertures 1009 in order toimplement at least some of the functionality shown in the fluid system510 of FIG. 5.

The cartridge 1000 can include a pouch space (not shown) that cancomprise one or more components of the fluid system 510. For example,one or more pouches and/or bladders can be disposed in the pouch space(not shown). In some embodiments, a cleaner pouch and/or a waste bladdercan be housed in a pouch space. The waste bladder can be placed underthe cleaner pouch such that, as detergent is removed from the cleanerpouch, the waste bladder has more room to fill. The components placed inthe pouch space (not shown) can also be placed side-by-side or in anyother suitable configuration.

The cartridge 1000 can include one or more pumps 1016 that facilitatemovement of fluid within the fluid system 510. Each of the pump housings1016 can contain, for example, a syringe pump having a plunger. Theplunger can be configured to interface with an actuator outside thecartridge 1000. For example, a portion of the pump that interfaces withan actuator can be exposed to the exterior of the cartridge 1000 housingby one or more apertures 1018 in the housing.

The cartridge 1000 can have an optical interface portion 1030 that isconfigured to interface with (or comprise a portion of) an opticalsystem. In the illustrated embodiment, the optical interface portion1030 can pivot around a pivot structure 1032. The optical interfaceportion 1030 can house a sample holder (not shown) in a chamber that canallow the sample holder to rotate. The sample holder can be held by acentrifuge interface 1036 that can be configured to engage a centrifugemotor (not shown). When the cartridge 1000 is being inserted into asystem, the orientation of the optical interface portion 1030 can bedifferent than when it is functioning within the system.

In some embodiments, the cartridge 1000 is designed for single patientuse. The cartridge 1000 may also be disposable and/or designed forreplacement after a period of operation. For example, in someembodiments, if the cartridge 1000 is installed in a continuouslyoperating monitoring device that performs four measurements per hour,the waste bladder may become filled or the detergent in the cleanerpouch depleted after about three days. The cartridge 1000 can bereplaced before the detergent and waste bladder are exhausted. In someembodiments, a portion of the cartridge 1000 can be disposable whileanother portion of the cartridge 1000 is disposable, but lasts longerbefore being discarded. In some embodiments, a portion of the cartridge1000 may not be disposable at all. For example, a portion thereof may beconfigured to be cleaned thoroughly and reused for different patients.Various combinations of disposable and less- or non-disposable portionsare possible.

The cartridge 1000 can be configured for easy replacement. For example,in some embodiments, the cartridge 1000 is designed to have aninstallation time of only minutes. For example, the cartridge can bedesigned to be installed in less than about five minutes, or less thantwo minutes. During installation, various fluid lines contained in thecartridge 1000 can be primed by automatically filling the fluid lineswith saline. The saline can be mixed with detergent powder from thecleaner pouch in order to create a cleaning solution.

The cartridge 1000 can also be designed to have a relatively brief shutdown time. For example, the shut down process can be configured to takeless than about fifteen minutes, or less than about ten minutes, or lessthan about five minutes. The shut down process can include flushing thepatient line; sealing off the insulin pump connection, the saline sourceconnection, and the sample source connection; and taking other steps todecrease the risk that fluids within the used cartridge 1000 will leakafter disconnection from the monitoring device.

Some embodiments of the cartridge 1000 can comprise a flat package tofacilitate packaging, shipping, sterilizing, etc. Advantageously,however, some embodiments can further comprise a hinge or other pivotstructure. Thus, as illustrated, an optical interface portion 1030 canbe pivoted around a pivot structure 1032 to generally align with theother portions of the cartridge 1000. The cartridge can be provided to amedical provider sealed in a removable wrapper, for example.

In some embodiments, the cartridge 1000 is designed to fit withinstandard waste containers found in a hospital, such as a standardbiohazard container. For example, the cartridge 1000 can be less thanone foot long, less than one foot wide, and less than two inches thick.In some embodiments, the cartridge 1000 is designed to withstand asubstantial impact, such as that caused by hitting the ground after afour foot drop, without damage to the housing or internal components. Insome embodiments, the cartridge 1000 is designed to withstandsignificant clamping force applied to its casing. For example, thecartridge 1000 can be built to withstand five pounds per square inch offorce without damage. In some embodiments, the cartridge 1000 can bedesigned to be less sturdy and more biodegradable. In some embodiments,the cartridge 1000 can be formed and configured to withstand more orless than five pounds of force per square inch without damage. In someembodiments, the cartridge 1000 is non pyrogenic and/or latex free.

FIG. 11 illustrates an embodiment of a fluid-routing card 1038 that canbe part of the removable cartridge of FIG. 10. For example, thefluid-routing card 1038 can be located generally within the tubingportion 1008 of the cartridge 1000. The fluid-routing card 1038 cancontain various passages and/or tubes through which fluid can flow asdescribed with respect to FIG. 5 and/or FIG. 6, for example. Thus, theillustrated tube opening openings can be in fluid communication with thefollowing fluidic components, for example:

Tube Opening Reference Numeral Can Be In Fluid Communication With 1142third pump 568 (pump #3) 1144 infusion pump 518 1146 Presx 1148 air pump1150 Vent 1152 detergent (e.g., tergazyme) source or waste tube 1154Presx 1156 detergent (e.g., tergazyme) source or waste tube 1158 wastereceptacle 1160 first pump 522 (pump #1) (e.g., a saline pump) 1162saline source or waste tube 1164 anticoagulant (e.g., heparin) pump (seeFIG. 6) and/or shuttle valve 1166 detergent (e.g., tergazyme) source orwaste tube 1167 Presx 1168 Arrival sensor tube 528 (T4) 1169 tube 536(T2) 1170 Arrival sensor tube 528 (T4) 1171 Arrival sensor tube 528 (T4)1172 anticoagulant (e.g., heparin) pump 1173 T17 (see FIG. 6) 1174Sample cell holder interface tube 582 (N1) 1176 anticoagulant valve tube534 (T3) 1178 Sample cell holder interface tube 584 (N2) 1180 T17 (seeFIG. 6) 1182 anticoagulant valve tube 534 (T3) 1184 Arrival sensor tube528 (T4) 1186 tube 536 (T2) 1188 anticoagulant valve tube 534 (T3) 1190anticoagulant valve tube 534 (T3)

The depicted fluid-routing card 1038 can have additional openings thatallow operative portions of actuators and/or valves to protrude throughthe fluid-routing card 1038 and interface with the tubes.

FIG. 12 illustrates how actuators, which can sandwich the fluid-routingcard 1038 between them, can interface with the fluid-routing card 1038of FIG. 11. Pinch valves 812 can have an actuator portion that protrudesaway from the fluid-routing card 1038 containing a motor. Each motor cancorrespond to a pinch platen 1202, which can be inserted into a pinchplaten receiving hole 1204. Similarly, sensors, such as a bubble sensor1206 can be inserted into receiving holes (e.g., the bubble sensorreceiving hole 1208). Movement of the pinch valves 812 can be detectedby the position sensors 1210.

FIG. 13 illustrates an actuator 808 that is connected to a correspondingsyringe body 810. The actuator 808 is an example of one of the actuators808 that is illustrated in FIG. 8 and in FIG. 9, and the syringe body810 is an example of one of the syringe bodies 810 that are visible inFIG. 8 and in FIG. 9. A ledge portion 1212 of the syringe body 810 canbe engaged (e.g., slid into) a corresponding receiving portion 1214 inthe actuator 808. In some embodiments, the receiving portion 1214 canslide outward to engage the stationary ledge portion 1212 after thedisposable cartridge 804 is in place. Similarly, a receiving tube 1222in the syringe plunger 1223 can be slide onto (or can receive) aprotruding portion 1224 of the actuator 808. The protruding portion 1224can slide along a track 1226 under the influence of a motor inside theactuator 808, thus actuating the syringe plunger 1223 and causing fluidto flow into or out of the syringe tip 1230.

FIG. 14 shows a rear perspective view of internal scaffolding 1231 andthe protruding bodies of some pinch valves 812. The internal scaffolding1231 can be formed from metal and can provide structural rigidity andsupport for other components. The scaffolding 1231 can have holes 1232into which screws can be screwed or other connectors can be inserted. Insome embodiments, a pair of sliding rails 1234 can allow relativemovement between portions of an analyzer. For example, a slidableportion 1236 (which can correspond to the movable portion 706, forexample) can be temporarily slid away from the scaffolding 1231 of amain unit in order to allow an insertable portion (e.g., the cartridge804) to be inserted.

FIG. 15 shows an underneath perspective view of the sample cell holder820, which is attached to the centrifuge interface 1036. The sample cellholder 820 can have an opposite side (see FIG. 17) that allows it toslide into a receiving portion of the centrifuge interface 1036. Thesample cell holder 820 can also have receiving nubs 1512A that provide apathway into a sample cell 1548 held by the sample cell holder 820.Receiving nubs 1512B can provide access to a shunt 1586 (see FIG. 16)inside the sample cell holder 820. The receiving nubs 1512A and 1512Bcan receive and or dock with fluid nipples 1514. The fluid nipples 1514can protrude at an angle from the sample injector 1006, which can inturn protrude from the cartridge 1000 (see FIG. 10). The tubes 1516shown protruding from the other end of the sample injector 1006 can bein fluid communication with the sample cell holder interface tubes 582(N1) and 584 (N2) (see FIG. 5 and FIG. 6), as well as 1074 and 1078 (seeFIG. 11).

FIG. 16 shows a plan view of the sample cell holder 820 with hiddenand/or non-surface portions illustrated using dashed lines. Thereceiving nubs 1512A communicate with passages 1550 inside the samplecell 1548 (which can correspond, for example to the sample cell 548 ofFIG. 5). The passages widen out into a wider portion 1552 thatcorresponds to a window 1556. The window 1556 and the wider portion 1552can be configured to house the sample when radiation is emitted along apathlength that is generally non-parallel to the sample cell 1548. Thewindow 1556 can allow calibration of the instrument with the sample cell1548 in place, even before a sample has arrived in the wider portion1552.

An opposite opening 1530 can provide an alternative optical pathwaybetween a radiation source and a radiation detector (e.g., the radiationsource 826 of FIG. 18) and may be used, for example, for obtaining acalibration measurement of the source and detector without anintervening window or sample. Thus, the opposite opening 1530 can belocated generally at the same radial distance from the axis of rotationas the window 1556.

The receiving nubs 1512B communicate with a shunt passage 1586 insidethe sample cell holder 820 (which can correspond, for example to theshunt 586 of FIG. 5).

Other features of the sample cell holder 820 can provide balancingproperties for even rotation of the sample cell holder 820. For example,the wide trough 1562 and the narrower trough 1564 can be sized orotherwise configured so that the weight and/or mass of the sample cellholder 820 is evenly distributed from left to right in the view of FIG.16, and/or from top to bottom in this view of FIG. 16.

FIG. 17 shows a top perspective view of the centrifuge interface 1036connected to the sample cell holder 820. The centrifuge interface 1036can have a bulkhead 1520 with a rounded slot 1522 into which anactuating portion of a centrifuge can be slid from the side. Thecentrifuge interface 1036 can thus be spun about an axis 1524, alongwith the sample cell holder 820, causing fluid (e.g., whole blood)within the sample cell 1548 to separate into concentric strata,according to relative density of the fluid components (e.g., plasma, redblood cells, buffy coat, etc.), within the sample cell 1548. The samplecell holder 820 can be transparent, or it can at least have transparentportions (e.g., the window 1556 and/or the opposite opening 1530)through which radiation can pass, and which can be aligned with anoptical pathway between a radiation source and a radiation detector(see, e.g., FIG. 20). In addition, a round opening 1530 throughcentrifuge rotor 1520 provides an optical pathway between the radiationsource and radiation detector and may be used, for example, forobtaining a calibration measurement of the source and detector withoutan intervening window or sample.

FIG. 18 shows a perspective view of an example optical system 803. Sucha system can be integrated with other systems as shown in FIG. 9, forexample. The optical system 803 can fill the role of the optical system412, and it can be integrated with and/or adjacent to a fluid system(e.g., the fluid-handling system 404 or the fluid system 801). Thesample cell holder 820 can be seen attached to the centrifuge interface1036, which is in turn connected to, and rotatable by the centrifugemotor 818. A filter wheel housing 1812 is attached to the filter wheelmotor 822 and encloses a filter wheel 1814. A protruding shaft assembly1816 can be connected to the filter wheel 1814. The filter wheel 1814can have multiple filters (see FIG. 19). The radiation source 826 isaligned to transmit radiation through a filter in the filter wheel 1814and then through a portion of the sample cell holder 820. Transmittedand/or reflected and/or scattered radiation can then be detected by aradiation detector.

FIG. 19 shows a view of the filter wheel 1814 when it is not locatedwithin the filter wheel housing 1812 of the optical system 803.Additional features of the protruding shaft assembly 1816 can be seen,along with multiple filters 1820. In some embodiments, the filters 1820can be removably and/or replaceably inserted into the filter wheel 1814.

Spectroscopic System

As described above with reference to FIG. 4, the system 400 comprisesthe optical system 412 for analysis of a fluid sample. In variousembodiments, the optical system 412 comprises one or more opticalcomponents including, for example, a spectrometer, a photometer, areflectometer, or any other suitable device for measuring opticalproperties of the fluid sample. The optical system 412 may perform oneor more optical measurements on the fluid sample including, for example,measurements of transmittance, absorbance, reflectance, scattering,and/or polarization. The optical measurements may be performed in one ormore wavelength ranges including, for example, infrared (IR) and/oroptical wavelengths. As described with reference to FIG. 4 (and furtherdescribed below), the measurements from the optical system 412 arecommunicated to the algorithm processor 416 for analysis. For example,in some embodiments the algorithm processor 416 computes concentrationof analyte(s) (and/or interferent(s)) of interest in the fluid sample.Analytes of interest can include, for example, glucose and/or lactate inwhole blood and/or in blood plasma. In some embodiments the algorithmprocessor 416 can advantageously calibrate a measured analyteconcentration for some or all of the effects of sample dilution. In someembodiments, the algorithm processor 416 may correct a measured analyteconcentration for dilution to provide an estimate of analyteconcentration that is more representative of the concentration in thepatient's body than would otherwise be the case without correcting fordilution.

FIG. 20 schematically illustrates an embodiment of the optical system412 that comprises a spectroscopic analyzer 2010 adapted to measurespectra of a fluid sample such as, for example, blood or blood plasma.The analyzer 2010 comprises an energy source 2012 disposed along anoptical axis X of the analyzer 2010. When activated, the energy source2012 generates an electromagnetic energy beam E, which advances from theenergy source 2012 along the optical axis X. In some embodiments, theenergy source 2012 comprises an infrared energy source, and the energybeam E comprises an infrared beam. In some embodiments, the infraredenergy beam E comprises a mid-infrared energy beam or a near-infraredenergy beam. In some embodiments, the energy beam E can include opticaland/or radio frequency wavelengths.

The energy source 2012 may comprise a broad-band and/or a narrow-bandsource of electromagnetic energy. In some embodiments, the energy source2012 comprises optical elements such as, e.g., filters, collimators,lenses, mirrors, etc., that are adapted to produce a desired energy beamE. For example, in some embodiments, the energy beam E is an infraredbeam in a wavelength range between about 2 μm and 20 m. In someembodiments, the energy beam E comprises an infrared beam in awavelength range between about 4 μm and 10 μm. In the infraredwavelength range, water generally is the main contributor to the totalabsorption together with features from absorption of other bloodcomponents, particularly in the 6 μm-10 μm range. The 4 μm to 10 μmwavelength band has been found to be advantageous for determiningglucose concentration, because glucose has a strong absorption peakstructure from about 8.5 μm to 10 μm, whereas most other bloodcomponents have a relatively low and flat absorption spectrum in the 8.5μm to 10 μm range. Two exceptions are water and hemoglobin, which areinterferents in this range.

The energy beam E may be temporally modulated to provide increasedsignal-to-noise ratio (S/N) of the measurements provided by the analyzer2010 as further described below. For example, in some embodiments, thebeam E is modulated at a frequency of about 10 Hz or in a range fromabout 1 Hz to about 30 Hz. A suitable energy source 2012 may be anelectrically modulated thin-film thermoresistive element such as theHawkEye IR-50 available from Hawkeye Technologies of Milford, Conn.

As depicted in FIG. 20, the energy beam E propagates along the opticalaxis X and passes through an aperture 2014 and a filter 2015 therebyproviding a filtered energy beam E_(f). The aperture 2014 helpscollimate the energy beam E and can include one or more filters adaptedto reduce the filtering burden of the filter 2015. For example, theaperture 2014 may comprise a broadband filter that substantiallyattenuates beam energy outside a wavelength band between about 4 μm toabout 10 μm. The filter 2015 may comprise a narrow-band filter thatsubstantially attenuates beam energy having wavelengths outside of afilter passband (which may be tunable or user-selectable in someembodiments). The filter passband may be specified by a half-powerbandwidth (“HPBW”). In some embodiments, the filter 2015 may have anHPBW in a range from about 0.1 μm to about 2 μm, or 0.01 μm to about 1μm. In some embodiments, the bandwidths are in a range from about 0.2 μmto 0.5 μm, or 0.1 μm to 0.35 μm. Other filter bandwidths may be used.The filter 2015 may comprise a varying-passband filter, anelectronically tunable filter, a liquid crystal filter, an interferencefilter, and/or a gradient filter. In some embodiments, the filter 2015comprises one or a combination of a grating, a prism, a monochrometer, aFabry-Perot etalon, and/or a polarizer. Other optical elements may beutilized as well.

In the embodiment shown in FIG. 20, the analyzer 2010 comprises a filterwheel assembly 2021 configured to dispose one or more filters 2015 alongthe optical axis X. The filter wheel assembly 2021 comprises a filterwheel 2018, a filter wheel motor 2016, and a position sensor 2020. Thefilter wheel 2018 may be substantially circular and have one or morefilters 2015 or other optical elements (e.g., apertures, gratings,polarizers, mirrors, etc.) disposed around the circumference of thewheel 2018. In some embodiments, the number of filters 2015 in thefilter wheel 2016 may be, for example, 1, 2, 5, 10, 15, 20, 25, or more.The motor 2016 is configured to rotate the filter wheel 2018 to disposea desired filter 2015 (or other optical element) in the energy beam E soas to produce the filtered beam E_(f). In some embodiments, the motor2016 comprises a stepper motor. The position sensor 2020 determines theangular position of the filter wheel 2016, and communicates acorresponding filter wheel position signal to the algorithm processor416, thereby indicating which filter 2015 is in position on the opticalaxis X. In various embodiments, the position sensor 2020 may be amechanical, optical, and/or magnetic encoder. An alternative to thefilter wheel 2018 is a linear filter translated by a motor. The linearfilter can include an array of separate filters or a single filter withproperties that change along a linear dimension.

The filter wheel motor 2016 rotates the filter wheel 2018 to positionthe filters 2015 in the energy beam E to sequentially vary thewavelengths or the wavelength bands used to analyze the fluid sample. Insome embodiments, each individual filter 2015 is disposed in the energybeam E for a dwell time during which optical properties in the passbandof the filter are measured for the sample. The filter wheel motor 2016then rotates the filter wheel 2018 to position another filter 2015 inthe beam E. In some embodiments, 25 narrow-band filters are used in thefilter wheel 2018, and the dwell time is about 2 seconds for each filter2015. A set of optical measurements for all the filters can be taken inabout 2 minutes, including sampling time and filter wheel movement. Insome embodiments, the dwell time may be different for different filters2015, for example, to provide a substantially similar S/N ratio for eachfilter measurement. Accordingly, the filter wheel assembly 2021functions as a varying-passband filter that allows optical properties ofthe sample to be analyzed at a number of wavelengths or wavelength bandsin a sequential manner.

In some embodiments of the analyzer 2010, the filter wheel 2018 includes25 finite-bandwidth infrared filters having a Gaussian transmissionprofile and full-width half-maximum (FWHM) bandwidth of 28 cm⁻¹corresponding to a bandwidth that varies from 0.14 μm at 7.08 μm to 0.28μm at 10 μm. The central wavelength of the filters are, in microns:7.082, 7.158, 7.241, 7.331, 7.424, 7.513, 7.605, 7.704, 7.800, 7.905,8.019, 8.150, 8.271, 8.598, 8.718, 8.834, 8.969, 9.099, 9.217, 9.346,9.461, 9.579, 9.718, 9.862, and 9.990.

With further reference to FIG. 20, the filtered energy beam E_(f)propagates to a beamsplitter 2022 disposed along the optical axis X. Thebeamsplitter 2022 separates the filtered energy beam E_(f) into a samplebeam E_(s) and a reference beam E_(r). The reference beam E_(r)propagates along a minor optical axis Y, which in this embodiment issubstantially orthogonal to the optical axis X. The energies in thesample beam E_(s) and the reference beam E_(r) may comprise any suitablefraction of the energy in the filtered beam E_(f). For example, in someembodiments, the sample beam E_(s) comprises about 80%, and thereference beam E_(r) comprises about 20%, of the filtered beam energyE_(f). A reference detector 2036 is positioned along the minor opticalaxis Y. An optical element 2034, such as a lens, may be used to focus orcollimate the reference beam E_(r) onto the reference detector 2036. Thereference detector 2036 provides a reference signal, which can be usedto monitor fluctuations in the intensity of the energy beam E emitted bythe source 2012. Such fluctuations may be due to drift effects, aging,wear, or other imperfections in the source 2012. The algorithm processor416 may utilize the reference signal to identify changes in propertiesof the sample beam E_(s) that are attributable to changes in theemission from the source 2012 and not to the properties of the fluidsample. By so doing, the analyzer 2010 may advantageously reducepossible sources of error in the calculated properties of the fluidsample (e.g., concentration). In other embodiments of the analyzer 2010,the beamsplitter 2022 is not used, and substantially all of the filteredenergy beam E_(f) propagates to the fluid sample.

As illustrated in FIG. 20, the sample beam E_(s) propagates along theoptical axis X, and a relay lens 2024 transmits the sample beam E_(s)into a sample cell 2048 so that at least a fraction of the sample beamE_(s) is transmitted through at least a portion of the fluid sample inthe sample cell 2048. A sample detector 2030 is positioned along theoptical axis X to measure the sample beam E_(s) that has passed throughthe portion of the fluid sample. An optical element 2028, such as alens, may be used to focus or collimate the sample beam E_(s) onto thesample detector 2030. The sample detector 2030 provides a sample signalthat can be used by the algorithm processor 416 as part of the sampleanalysis.

In the embodiment of the analyzer 2010 shown in FIG. 20, the sample cell2048 is located toward the outer circumference of the centrifuge wheel2050 (which can correspond, for example, to the sample cell holder 820described herein). The sample cell 2048 preferably comprises windowsthat are substantially transmissive to energy in the sample beam E_(s).For example, in implementations using mid-infrared energy, the windowsmay comprise calcium fluoride. As described herein with reference toFIG. 5, the sample cell 2048 is in fluid communication with an injectorsystem that permits filling the sample cell 2048 with a fluid sample(e.g., whole blood) and flushing the sample cell 2048 (e.g., with salineor a detergent). The injector system may disconnect after filling thesample cell 2048 with the fluid sample to permit free spinning of thecentrifuge wheel 2050.

The centrifuge wheel 2050 can be spun by a centrifuge motor 2026. Insome embodiments of the analyzer 2010, the fluid sample (e.g., a wholeblood sample) is spun at a certain number of revolutions per minute(RPM) for a given length of time to separate blood plasma for spectralanalysis. In some embodiments, the fluid sample is spun at about 7200RPM. In some embodiments, the fluid sample is spun at about 5000 RPM or4500 RPM. In some embodiments, the fluid sample is spun at more than onerate for successive time periods. The length of time can beapproximately 5 minutes. In some embodiments, the length of time isapproximately 2 minutes. In some embodiments, an anti-clotting agentsuch as heparin may be added to the fluid sample before centrifuging toreduce clotting. With reference to FIG. 20, the centrifuge wheel 2050 isrotated to a position where the sample cell 2048 intercepts the samplebeam E_(s), allowing energy to pass through the sample cell 2048 to thesample detector 2030.

The embodiment of the analyzer 2010 illustrated in FIG. 20advantageously permits direct measurement of the concentration ofanalytes in the plasma sample rather than by inference of theconcentration from measurements of a whole blood sample. An additionaladvantage is that relatively small volumes of fluid may bespectroscopically analyzed. For example, in some embodiments the fluidsample volume is between about 1 μL and 80 μL and is about 25 μL in someembodiments. In some embodiments, the sample cell 2048 is disposable andis intended for use with a single patient or for a single measurement.

In some embodiments, the reference detector 2036 and the sample detector2030 comprise broadband pyroelectric detectors. As known in the art,some pyroelectric detectors are sensitive to vibrations. Thus, forexample, the output of a pyroelectric infrared detector is the sum ofthe exposure to infrared radiation and to vibrations of the detector.The sensitivity to vibrations, also known as “microphonics,” canintroduce a noise component to the measurement of the reference andsample energy beams E_(r), E_(s) using some pyroelectric infrareddetectors. Because it may be desirable for the analyzer 2010 to providehigh signal-to-noise ratio measurements, such as, e.g., S/N in excess of100 dB, some embodiments of the analyzer 2010 utilize one or morevibrational noise reduction apparatus or methods. For example, theanalyzer 2010 may be mechanically isolated so that high S/Nspectroscopic measurements can be obtained for vibrations below anacceleration of about 1.5 G.

In some embodiments of the analyzer 2010, vibrational noise can bereduced by using a temporally modulated energy source 2012 combined withan output filter. In some embodiments, the energy source 2012 ismodulated at a known source frequency, and measurements made by thedetectors 2036 and 2030 are filtered using a narrowband filter centeredat the source frequency. For example, in some embodiments, the energyoutput of the source 2012 is sinusoidally modulated at 10 Hz, andoutputs of the detectors 2036 and 2030 are filtered using a narrowbandpass filter of less than about 1 Hz centered at 10 Hz. Accordingly,microphonic signals that are not at 10 Hz are significantly attenuated.In some embodiments, the modulation depth of the energy beam E may begreater than 50% such as, for example, 80%. The duty cycle of the beammay be between about 30% and 70%. The temporal modulation may besinusoidal or any other waveform. In embodiments utilizing temporallymodulated energy sources, detector output may be filtered using asynchronous demodulator and digital filter. The demodulator and filterare software components that may be digitally implemented in a processorsuch as the algorithm processor 416. Synchronous demodulators, coupledwith low pass filters, are often referred to as “lock in amplifiers.”

The analyzer 2010 may also include a vibration sensor 2032 (e.g., one ormore accelerometers) disposed near one (or both) of the detectors 2036and 2030. The output of the vibration sensor 2032 is monitored, andsuitable actions are taken if the measured vibration exceeds a vibrationthreshold. For example, in some embodiments, if the vibration sensor2032 detects above-threshold vibrations, the system discards any ongoingmeasurement and “holds off” on performing further measurements until thevibrations drop below the threshold. Discarded measurements may berepeated after the vibrations drop below the vibration threshold. Insome embodiments, if the duration of the “hold off” is sufficientlylong, the fluid in the sample cell 2030 is flushed, and a new fluidsample is delivered to the cell 2030 for measurement. The vibrationthreshold may be selected so that the error in analyte measurement is atan acceptable level for vibrations below the threshold. In someembodiments, the threshold corresponds to an error in glucoseconcentration of 5 mg/dL. The vibration threshold may be determinedindividually for each filter 2015.

Certain embodiments of the analyzer 2010 include a temperature system(not shown in FIG. 20) for monitoring and/or regulating the temperatureof system components (such as the detectors 2036, 2030) and/or the fluidsample. Such a temperature system can include temperature sensors,thermoelectrical heat pumps (e.g., a Peltier device), and/orthermistors, as well as a control system for monitoring and/orregulating temperature. In some embodiments, the control systemcomprises a proportional-plus-integral-plus-derivative (PID) control.For example, in some embodiments, the temperature system is used toregulate the temperature of the detectors 2030, 2036 to a desiredoperating temperature, such as 35 degrees Celsius.

Optical Measurement

The analyzer 2010 illustrated in FIG. 20 can be used to determineoptical properties of a substance in the sample cell 2048. The substancecan include whole blood, plasma, saline, water, air or other substances.In some embodiments, the optical properties include measurements of anabsorbance, transmittance, and/or optical density in the wavelengthpassbands of some or all of the filters 2015 disposed in the filterwheel 2018. As described above, a measurement cycle comprises disposingone or more filters 2015 in the energy beam E for a dwell time andmeasuring a reference signal with the reference detector 2036 and asample signal with the sample detector 2030. The number of filters 2015used in the measurement cycle will be denoted by N, and each filter 2015passes energy in a passband around a center wavelength λ_(i), where i isan index ranging over the number of filters (e.g., from 1 to N). The setof optical measurements from the sample detector 2036 in the passbandsof the N filters 2015 provide a wavelength-dependent spectrum of thesubstance in the sample cell 2048. The spectrum will be denoted byC_(s)(λ_(i)), where C_(s) may be a transmittance, absorbance, opticaldensity, or some other measure of an optical property of the substance.In some embodiments, the spectrum is normalized with respect to one ormore of the reference signals measured by the reference detector 2030and/or with respect to spectra of a reference substance (e.g., air orsaline). The measured spectra are communicated to the algorithmprocessor 416 for calculation of the concentration of the analyte(s) ofinterest in the fluid sample.

In some embodiments, the analyzer 2010 performs spectroscopicmeasurements on the fluid sample (known as a “wet” reading) and on oneor more reference samples. For example, an “air” reading occurs when thesample detector 2036 measures the sample signal without the sample cell2048 in place along the optical axis X. (This can occur, for example,when the opposite opening 1530 is aligned with the optical axis X). A“water” or “saline” reading occurs when the sample cell 2048 is filledwith water or saline, respectively. The algorithm processor 416 may beprogrammed to calculate analyte concentration using a combination ofthese spectral measurements. In some embodiments, an advantage ofcombining the “wet reading” with at least the “water” or “saline”reading is to calibrate a measured analyte concentration for some or allof the effects of dilution.

In some embodiments, a pathlength corrected spectrum is calculated usingwet, air, and reference readings. For example, the transmittance atwavelength λ_(i), denoted by T_(i), may be calculated according toT_(i)=(S_(i)(wet)/R_(i)(wet))/(S_(i)(air)/R_(i)(air)), where S_(i)denotes the sample signal from the sample detector 2036 and R_(i)denotes the corresponding reference signal from the reference detector2030. In some embodiments, the algorithm processor 416 calculates theoptical density, OD_(i), as a logarithm of the transmittance, e.g.,according to OD_(i)=−Log(T_(i)). In one implementation, the analyzer2010 takes a set of wet readings in each of the N filter passbands andthen takes a set of air readings in each of the N filter passbands. Inother embodiments, the analyzer 2010 may take an air reading before (orafter) the corresponding wet reading.

The optical density OD_(i) is the product of the absorption coefficientat wavelength λ_(i), α_(i), times the pathlength L over which the sampleenergy beam E_(s) interacts with the substance in the sample cell 2048,e.g., OD_(i)=α_(i) L. The absorption coefficient α_(i) of a substancemay be written as the product of an absorptivity per mole times a molarconcentration of the substance. FIG. 20 schematically illustrates thepathlength L of the sample cell 2048. The pathlength L may be determinedfrom spectral measurements made when the sample cell 2048 is filled witha reference substance. For example, because the absorption coefficientfor water (or saline) is known, one or more water (or saline) readingscan be used to determine the pathlength L from measurements of thetransmittance (or optical density) through the cell 2048. In someembodiments, several readings are taken in different wavelengthpassbands, and a curve-fitting procedure is used to estimate a best-fitpathlength L. The pathlength L may be estimated using other methodsincluding, for example, measuring interference fringes of light passingthrough an empty sample cell 2048.

The pathlength L may be used to determine the absorption coefficients ofthe fluid sample at each wavelength. Molar concentration of an analyteof interest can be determined from the absorption coefficient and theknown molar absorptivity of the analyte. In some embodiments, a samplemeasurement cycle comprises a saline reading (at one or morewavelengths), a set of N wet readings (taken, for example, through asample cell 2048 containing saline solution), followed by a set of N airreadings (taken, for example, through the opposite opening 1530). Asdiscussed above, the sample measurement cycle can be performed in agiven length of time that may depend, at least in part, on filter dwelltimes. For example, the measurement cycle may take five minutes when thefilter dwell times are about five seconds. In some embodiments, themeasurement cycle may take about two minutes when the filter dwell timesare about two seconds. After the sample measurement cycle is completed,a detergent cleaner may be flushed through the sample cell 2048 toreduce buildup of organic matter (e.g., proteins) on the windows of thesample cell 2048. The detergent is then flushed to a waste bladder.

In some embodiments, the system stores information related to thespectral measurements so that the information is readily available forrecall by a user. The stored information can includewavelength-dependent spectral measurements (including fluid sample, air,and/or saline readings), computed analyte values, system temperaturesand electrical properties (e.g., voltages and currents), and any otherdata related to use of the system (e.g., system alerts, vibrationreadings, S/N ratios, etc.). The stored information may be retained inthe system for a time period such as, for example, 30 days. After thistime period, the stored information may be communicated to an archivaldata storage system and then deleted from the system. In someembodiments, the stored information is communicated to the archival datastorage system via wired or wireless methods, e.g., over a hospitalinformation system (HIS).

Analyte Analysis

The algorithm processor 416 (FIG. 4) (or any other suitable processor orprocessors) may be configured to receive from the analyzer 2010 thewavelength-dependent optical measurements Cs(λ_(i)) of the fluid sample.In some embodiments, the optical measurements comprise spectra such as,for example, optical densities OD_(i) measured in each of the N filterpassbands centered around wavelengths λ_(i). The optical measurementsCs(λ_(i)) are communicated to the processor 416, which analyzes theoptical measurements to detect and quantify one or more analytes in thepresence of interferents. In some embodiments, one or more poor qualityoptical measurements Cs(λ_(i)) are rejected (e.g., as having a S/N ratiothat is too low), and the analysis performed on the remaining,sufficiently high-quality measurements. In another embodiment,additional optical measurements of the fluid sample are taken by theanalyzer 2010 to replace one or more of the poor quality measurements.

Interferents can comprise components of a material sample being analyzedfor an analyte, where the presence of the interferent affects thequantification of the analyte. Thus, for example, in the spectroscopicanalysis of a sample to determine an analyte concentration, aninterferent could be a compound having spectroscopic features thatoverlap with those of the analyte, in at least a portion of thewavelength range of the measurements. The presence of such aninterferent can introduce errors in the quantification of the analyte.More specifically, the presence of one or more interferents can affectthe sensitivity of a measurement technique to the concentration ofanalytes of interest in a material sample, especially when the system iscalibrated in the absence of, or with an unknown amount of, theinterferent.

Independently of or in combination with the attributes of interferentsdescribed above, interferents can be classified as being endogenous(i.e., originating within the body) or exogenous (i.e., introduced fromor produced outside the body). As an example of these classes ofinterferents, consider the analysis of a blood sample (or a bloodcomponent sample or a blood plasma sample) for the analyte glucose.Endogenous interferents include those blood components having originswithin the body that affect the quantification of glucose, and caninclude water, hemoglobin, blood cells, and any other component thatnaturally occurs in blood. Exogenous interferents include those bloodcomponents having origins outside of the body that affect thequantification of glucose, and can include items administered to aperson, such as medicaments, drugs, foods or herbs, whether administeredorally, intravenously, topically, etc.

Independently of or in combination with the attributes of interferentsdescribed above, interferents can comprise components which arepossibly, but not necessarily, present in the sample type underanalysis. In the example of analyzing samples of blood or blood plasmadrawn from patients who are receiving medical treatment, a medicamentsuch as acetaminophen is possibly, but not necessarily, present in thissample type. In contrast, water is necessarily present in such blood orplasma samples.

Certain disclosed analysis methods are particularly effective if eachanalyte and interferent has a characteristic signature in themeasurement (e.g., a characteristic spectroscopic feature), and if themeasurement is approximately affine (e.g., includes a linear term and anoffset) with respect to the concentration of each analyte andinterferent. In such methods, a calibration process is used to determinea set of one or more calibration coefficients and a set of one or moreoptional offset values that permit the quantitative estimation of ananalyte. For example, the calibration coefficients and the offsets maybe used to calculate an analyte concentration from spectroscopicmeasurements of a material sample (e.g., the concentration of glucose inblood plasma). In some of these methods, the concentration of theanalyte is estimated by multiplying the calibration coefficient by ameasurement value (e.g., an optical density) to estimate theconcentration of the analyte. Both the calibration coefficient andmeasurement can comprise arrays of numbers. For example, in someembodiments, the measurement comprises spectra C_(s)(λ_(i)) measured atthe wavelengths λ_(i), and the calibration coefficient and optionaloffset comprise an array of values corresponding to each wavelengthλ_(i). In some embodiments, as further described below, a hybrid linearanalysis (HLA) technique is used to estimate analyte concentration inthe presence of a set of interferents, while retaining a high degree ofsensitivity to the desired analyte. The data used to accommodate the setof possible interferents can include (a) signatures of each of themembers of the family of potential additional substances and (b) atypical quantitative level at which each additional substance, ifpresent, is likely to appear. In some embodiments, the calibrationcoefficient (and optional offset) are adjusted to minimize or reduce thesensitivity of the calibration to the presence of interferents that areidentified as possibly being present in the fluid sample.

In some embodiments, the analyte analysis method uses a set of trainingspectra each having known analyte concentration and produces acalibration that minimizes the variation in estimated analyteconcentration with interferent concentration. The resulting calibrationcoefficient indicates sensitivity of the measurement to analyteconcentration. The training spectra need not include a spectrum from theindividual whose analyte concentration is to be determined. That is, theterm “training” when used in reference to the disclosed methods does notrequire training using measurements from the individual whose analyteconcentration will be estimated (e.g., by analyzing a bodily fluidsample drawn from the individual).

Several terms are used herein to describe the analyte analysis process.The term “Sample Population” is a broad term and includes, withoutlimitation, a large number of samples having measurements that are usedin the computation of calibration values (e.g., calibration coefficientsand optional offsets). In some embodiments, the term Sample Populationcomprises measurements (such as, e.g., spectra) from individuals and maycomprise one or more analyte measurements determined from those sameindividuals. Additional demographic information may be available for theindividuals whose sample measurements are included in the SamplePopulation. For an embodiment involving the spectroscopic determinationof glucose concentration, the Sample Population measurements may includea spectrum (measurement) and a glucose concentration (analytemeasurement).

Various embodiments of Sample Populations may be used in variousembodiments of the systems and methods described herein. Severalexamples of Sample Populations will now be described. These examples areintended to illustrate certain aspects of possible Sample Populationembodiments but are not intended to limit the types of SamplePopulations that may be generated. In certain embodiments, a SamplePopulation may include samples from one or more of the example SamplePopulations described below.

In some embodiments of the systems and methods described herein, one ormore Sample Populations are included in a “Population Database.” ThePopulation Database may be implemented and/or stored on acomputer-readable medium. In certain embodiments, the systems andmethods may access the Population Database using wired and/or wirelesstechniques. Certain embodiments may utilize several different PopulationDatabases that are accessible locally and/or remotely. In someembodiments, the Population Database includes one or more of the exampleSample Populations described below. In some embodiments, two or moredatabases can be combined into a single database, and in otherembodiments, any one database can be divided into multiple databases.

An example Sample Population may comprise samples from individualsbelonging to one or more demographic groups including, for example,ethnicity, nationality, gender, age, etc. Demographic groups may beestablished for any suitable set of one or more distinctive factors forthe group including, for example, medical, cultural, behavioral,biological, geographical, religious, and genealogical traits. Forexample, in certain embodiments, a Sample Population includes samplesfrom individuals from a specific ethnic group (e.g., Caucasians,Hispanics, Asians, African Americans, etc.). In another embodiment, aSample Population includes samples from individuals of a specific genderor a specific race. In some embodiments, a Sample Population includessamples from individuals belonging to more than one demographic group(e.g., samples from Caucasian women).

Another example Sample Population can comprise samples from individualshaving one or more medical conditions. For example, a Sample Populationmay include samples from individuals who are healthy and unmedicated(sometimes referred to as a Normal Population). In some embodiments, theSample Population includes samples from individuals having one or morehealth conditions (e.g., diabetes). In some embodiments, the SamplePopulation includes samples from individuals taking one or moremedications. In certain embodiments, Sample Population includes samplesfrom individuals diagnosed to have a certain medical condition or fromindividuals being treated for certain medical conditions or somecombination thereof The Sample Population may include samples fromindividuals such as, for example, ICU patients, maternity patients, andso forth.

An example Sample Population may comprise samples that have the sameinterferent or the same type of interferents. In some embodiments, aSample Population can comprise multiple samples, all lacking aninterferent or a type of interferent. For example, a Sample Populationmay comprise samples that have no exogenous interferents, that have oneor more exogenous interferents of either known or unknown concentration,and so forth. The number of interferents in a sample depends on themeasurement and analyte(s) of interest, and may number, in general, fromzero to a very large number (e.g., greater than 300). All of theinterferents typically are not expected to be present in a particularmaterial sample, and in many cases, a smaller number of interferents(e.g., 0, 1, 2, 5, 10, 15, 20, or 25) may be used in an analysis. Incertain embodiments, the number of interferents used in the analysis isless than or equal to the number of wavelength-dependent measurements Nin the spectrum Cs(λ_(i)).

Certain embodiments of the systems and methods described herein arecapable of analyzing a material sample using one or more SamplePopulations (e.g., accessed from the Population Database). Certain suchembodiments may use information regarding some or all of theinterferents which may or may not be present in the material sample. Insome embodiments, a list of one or more possible interferents, referredto herein as forming a “Library of Interferents,” can be compiled. Eachinterferent in the Library can be referred to as a “LibraryInterferent.” The Library Interferents may include exogenousinterferents and endogenous interferents that may be present in amaterial sample. For example, an interferent may be present due to amedical condition causing abnormally high concentrations of theexogenous and endogenous interferents. In some embodiments, the Libraryof Interferents may not include one or more interferents that are knownto be present in all samples. Thus, for example, water, which is aglucose interferent for many spectroscopic measurements, may not beincluded in the Library of Interferents. In certain embodiments, thesystems and methods use samples in the Sample Population to traincalibration methods.

The material sample being measured, for example a fluid sample in thesample cell 2048, may also include one or more Library Interferentswhich may include, but is not limited to, an exogenous interferent or anendogenous interferent. Examples of exogenous interferent can includemedications, and examples of endogenous interferents can include urea inpersons suffering from renal failure. In addition to componentsnaturally found in the blood, the ingestion or injection of somemedicines or illicit drugs can result in very high and rapidly changingconcentrations of exogenous interferents.

In some embodiments, measurements of a material sample (e.g., a bodilyfluid sample), samples in a Sample Population, and the LibraryInterferents comprise spectra (e.g., infrared spectra). The spectraobtained from a sample and/or an interferent may be temperaturedependent. In some embodiments, it may be beneficial to calibrate fortemperatures of the individual samples in the Sample Population or theinterferents in the Library of Interferents. In some embodiments, atemperature calibration procedure is used to generate a temperaturecalibration factor that substantially accounts for the sampletemperature. For example, the sample temperature can be measured, andthe temperature calibration factor can be applied to the SamplePopulation and/or the Library Interferent spectral data. In someembodiments, a water or saline spectrum is subtracted from the samplespectrum to account for temperature effects of water in the sample.

In other embodiments, temperature calibration may not be used. Forexample, if Library Interferent spectra, Sample Population spectra, andsample spectra are obtained at approximately the same temperature, anerror in a predicted analyte concentration may be within an acceptabletolerance. If the temperature at which a material sample spectrum ismeasured is within, or near, a temperature range (e.g., several degreesCelsius) at which the plurality of Sample Population spectra areobtained, then some analysis methods may be relatively insensitive totemperature variations. Temperature calibration may optionally be usedin such analysis methods.

Systems and Methods for Estimating Analyte Concentration in the Presenceof Interferents

FIG. 21 is a flowchart that schematically illustrates an embodiment of amethod 2100 for estimating the concentration of an analyte in thepresence of interferents. In block 2110, a measurement of a sample isobtained, and in block 2120 data relating to the obtained measurement isanalyzed to identify possible interferents to the analyte. In block2130, a model is generated for predicting the analyte concentration inthe presence of the identified possible interferents, and in block 2140the model is used to estimate the analyte concentration in the samplefrom the measurement. In certain embodiments of the method 2100, themodel generated in block 2130 is selected to reduce or minimize theeffect of identified interferents that are not present in a generalpopulation of which the sample is a member.

An example embodiment of the method 2100 of FIG. 21 for thedetermination of an analyte (e.g., glucose) in a blood sample will nowbe described. This example embodiment is intended to illustrate variousaspects of the method 2100 but is not intended as a limitation on thescope of the method 2100 or on the range of possible analytes. In thisexample, the sample measurement in block 2110 is an absorption spectrum,Cs(λ_(i)), of a measurement sample S that has, in general, one analyteof interest, glucose, and one or more interferents.

In block 2120, a statistical comparison of the absorption spectrum ofthe sample S with a spectrum of the Sample Population and combinationsof individual Library Interferent spectra is performed. The statisticalcomparison provides a list of Library Interferents that are possiblycontained in sample S and can include either no Library Interferents orone or more Library Interferents. In this example, in block 2130, one ormore sets of spectra are generated from spectra of the Sample Populationand their respective known analyte concentrations and known spectra ofthe Library Interferents identified in block 2120. In block 2130, thegenerated spectra are used to calculate a model for predicting theanalyte concentration from the obtained measurement. In someembodiments, the model comprises one or more calibration coefficientsκ(λ_(i)) that can be used with the sample measurements Cs(λ_(i)) toprovide an estimate of the analyte concentration, g_(est). In block2140, the estimated analyte concentration is determined form the modelgenerated in block 2130. For example, in some embodiments of HLA, theestimated analyte concentration is calculated according to a linearformula: g_(est)=κ(λ_(i))·C_(s)(λ_(i)). Because the absorptionmeasurements and calibration coefficients may represent arrays ofnumbers, the multiplication operation indicated in the preceding formulamay comprise a sum of the products of the measurements and coefficients(e.g., an inner product or a matrix product). In some embodiments, thecalibration coefficient is determined so as to have reduced or minimalsensitivity to the presence of the identified Library Interferents.

An example embodiment of block 2120 of the method 2100 will now bedescribed with reference to FIG. 22. In this example, block 2120includes forming a statistical Sample Population model (block 2210),assembling a library of interferent data (block 2220), assembling allsubsets of size K of the library interferents (block 2225), comparingthe obtained measurement and statistical Sample Population model withdata for each set of interferents from an interferent library (block2230), performing a statistical test for the presence of eachinterferent from the interferent library (block 2240), and identifyingpossible interferents that pass the statistical test (block 2250). Thesize K of the subsets may be an integer such as, for example, 1, 2, 3,4, 5, 6, 10, 16, or more. The acts of block 2220 can be performed onceor can be updated as necessary. In certain embodiments, the acts ofblocks 2230, 2240, and 2250 are performed sequentially for all subsetsof Library Interferents that pass the statistical test (block 2240). Inthis example, in block 2210, a Sample Population Database is formed thatincludes a statistically large Sample Population of individual spectrataken over the same wavelength range as the sample spectrum,C_(s)(λ_(i)). The Database also includes an analyte concentrationcorresponding to each spectrum. For example, if there are P SamplePopulation spectra, then the spectra in the Database can be representedas C={C₁, C₂, . . . , C_(P)}, and the analyte concentrationcorresponding to each spectrum can be represented as g={g₁, g₂, . . . ,g_(P)}. In some embodiments, the Sample Population does not have any ofthe Library Interferents present, and the material sample hasinterferents contained in the Sample Population and one or more of theLibrary Interferents.

In some embodiments of block 2210, the statistical sample modelcomprises a mean spectrum and a covariance matrix calculated for theSample Population. For example, if each spectrum measured at Nwavelengths λ_(i) is represented by an N×1 array, C, then the meanspectrum, μ, is an N×1 array having values at each wavelength averagedover the range of spectra in the Sample Population. The covariancematrix, V, is calculated as the expected value of the deviation betweenC and μ and can be written as V=E((C−μ) (C−μ)^(T)) where E(·) representsthe expected value and the superscript T denotes transpose. In otherembodiments, additional statistical parameters may be included in thestatistical model of the Sample Population spectra.

Additionally, a Library of Interferents may be assembled in block 2220.A number of possible interferents can be identified, for example, as alist of possible medications or foods that might be ingested by thepopulation of patients at issue. Spectra of these interferents can beobtained, and a range of expected interferent concentrations in theblood, or other expected sample material, can be estimated. In certainembodiments, the Library of Interferents includes, for each of “M”interferents, the absorption spectrum normalized to unit interferentconcentration of each interferent, IF={IF₁, IF₂, . . . , IF_(M)}, and arange of concentrations for each interferent from Tmax={Tmax₁, Tmax₂, .. . , Tmax_(M)) to Tmin={Tmin₁, Tmin₂, . . . , Tmin_(M)). Information inthe Library may be assembled once and accessed as needed. For example,the Library and the statistical model of the Sample Population may bestored in a storage device associated with the algorithm processor 416(see, FIG. 4).

Continuing in block 2225, the algorithm processor 416 assembles one ormore subsets comprising a number K of spectra taken from the Library ofInterferents. The number K may be an integer such as, for example, 1, 2,3, 4, 5, 6, 10, 16, or more. In some embodiments, the subsets compriseall combinations of the M Library spectra taken K at a time. In theseembodiments, the number of subsets having K spectra is M!/(K! (M−K)!),where ! represents the factorial function.

Continuing in block 2230, the obtained measurement data (e.g., thesample spectrum) and the statistical Sample Population model (e.g., themean spectrum and the covariance matrix) are compared with data for eachsubset of interferents determined in block 2225 in order to determinethe presence of possible interferents in the sample (block 2240). Insome embodiments, the statistical test for the presence of aninterferent subset in block 2240 comprises determining theconcentrations of each subset of interferences that minimize astatistical measure of “distance” between a modified spectrum of thematerial sample and the statistical model of the Sample Population(e.g., the mean μ and the covariance V). The term “concentration” usedin this context refers to a computed value, and, in some embodiments,that computed value may not correspond to an actual concentration. Theconcentrations may be calculated numerically. In some embodiments, theconcentrations are calculated by algebraically solving a set of linearequations. The statistical measure of distance may comprise thewell-known Mahalanobis distance (or square of the Mahalanobis distance)and/or some other suitable statistical distance metric (e.g.,Hotelling's T-square statistic). In certain implementations, themodified spectrum is given by C′_(s)(T)=C_(s)−IF·T where T=(T₁, T₂, . .. T_(K))^(T) is a K-dimensional column vector of interferentconcentrations and IF={IF₁, IF₂, . . . IF_(K)} represents the Kinterferent absorption spectra of the subset. In some embodiments,concentration of the i^(th) interferent is assumed to be in a range froma minimum value, Tmin_(i), to a maximum value, Tmax_(i). The value ofTmin_(i) may be zero, or may be a value between zero and Tmax_(i), suchas a fraction of Tmax_(i), or may be a negative value. Negative valuesrepresent interferent concentrations that are smaller than baselineinterferent values in the Sample Population.

In block 2250, a list of a number N_(S) of possible interferent subsetsξ may be identified as the particular subsets that pass one or morestatistical tests (in block 2240) for being present in the materialsample. One or more statistical tests may be used, alone or incombination, to identify the possible interferents. For example, if astatistical test indicates that an i^(th) interferent is present in aconcentration outside the range Tmin_(i) to Tmax_(i), then this resultmay be used to exclude the i^(th) interferent from the list of possibleinterferents. In some embodiments, only the single most probableinterferent subset is included on the list, for example, the subsethaving the smallest statistical distance (e.g., Mahalanobis distance).In an embodiment, the list includes the subsets ξ having statisticaldistances smaller than a threshold value. In certain embodiments, thelist includes a number N_(S) of subsets having the smallest statisticaldistances, e.g., the list comprises the “best” candidate subsets. Thenumber N_(S) may be any suitable integer such as 10, 20, 50, 100, 200,or more. An advantage of selecting the “best” N_(S) subsets is reducedcomputational burden on the algorithm processor 416. In someembodiments, the list includes all the Library Interferents. In certainsuch embodiments, the list is selected to comprise combinations of theN_(S) subsets taken L at a time. For example, in some embodiments, pairsof subsets are taken (e.g., L=2). An advantage of selecting pairs ofsubsets is that pairing captures the most likely combinations ofinterferents and the “best” candidates are included multiple times inthe list of possible interferents. In embodiments in which combinationsof L subsets are selected, the number of combinations of subsets in thelist of possible interferent subsets is N_(S)!/(L! (N_(S)−L)!).

In other embodiments, the list of possible interferent subsets ξ isdetermined using a combination of some or all of the above criteria. Inanother embodiment, the list of possible interferent subsets ξ includeseach of the subsets assembled in block 2225. Many selection criteria arepossible for the list of possible interferent subsets ξ.

Returning to FIG. 21, the method 2100 continues in block 2130 whereanalyte concentration is estimated in the presence of the possibleinterferent subsets ξ determined in block 2250. FIG. 23 is a flowchartthat schematically illustrates an example embodiment of the acts ofblock 2130. In block 2310, synthesized Sample Population measurementsare generated to form an Interferent Enhanced Spectral Database (IESD).In block 2360, the IESD and known analyte concentrations are used togenerate calibration coefficients for the selected interferent subset.As indicated in block 2365, blocks 2310 and 2360 may be repeated foreach interferent subset ξ identified in the list of possible interferentsubsets (e.g., in block 2250 of FIG. 22). In this example embodiment,when all the interferent subsets ξ have been processed, the methodcontinues in block 2370, wherein an average calibration coefficient isapplied to the measured spectra to determine a set of analyteconcentrations.

In one example embodiment for block 2310, synthesized Sample Populationspectra are generated by adding random concentrations of eachinterferent in one of the possible interferent subsets ξ. These spectraare referred to herein as an Interferent-Enhanced Spectral Database orIESD. In one example method, the IESD is formed as follows. A pluralityof Randomly-Scaled Single Interferent Spectra (RSIS) are formed for eachinterferent in the interferent subset ξ. Each RSIS is formed bycombinations of the interferent having spectrum IF multiplied by themaximum concentration Tmax, which is scaled by a random factor betweenzero and one. In certain embodiments, the scaling places the maximumconcentration at the 95^(th) percentile of a log-normal distribution inorder to generate a wide range of concentrations. In some embodiments,the log-normal distribution has a standard deviation equal to half ofits mean value.

In this example method, individual RSIS are then combined independentlyand in random combinations to form a large family of CombinationInterferent Spectra (CIS), with each spectrum in the CIS comprising arandom combination of RSIS, selected from the full set of identifiedLibrary Interferents. An advantage of this method of selecting the CISis that it produces adequate variability with respect to eachinterferent, independently across separate interferents.

The CIS and replicates of the Sample Population spectra are combined toform the IESD. Since the interferent spectra and the Sample Populationspectra may have been obtained from measurements having differentoptical pathlengths, the CIS may be scaled to the same pathlength as theSample Population spectra. The Sample Population Database is thenreplicated R times, where R depends on factors including the size of theDatabase and the number of interferents. The IESD includes R copies ofeach of the Sample Population spectra, where one copy is the originalSample Population Data, and the remaining R-1 copies each have onerandomly chosen CIS spectra added. Accordingly, each of the IESD spectrahas an associated analyte concentration from the Sample Populationspectra used to form the particular IESD spectrum. In some embodiments,a 10-fold replication of the Sample Population Database is used for 130Sample Population spectra obtained from 58 different individuals and 18Library Interferents. A smaller replication factor may be used if thereis greater spectral variety among the Library Interferent spectra, and alarger replication factor may be used if there is a greater number ofLibrary Interferents.

After the IESD is generated in block 2310, in block 2360, the IESDspectra and the known, random concentrations of the subset interferentsare used to generate a calibration coefficient for estimating theanalyte concentration from a sample measurement. The calibrationcoefficient is calculated in some embodiments using a hybrid linearanalysis (HLA) technique. In certain embodiments, the HLA technique usesa reference analyte spectrum to construct a set of spectra that are freeof the desired analyte, projecting the analyte's spectrum orthogonallyaway from the space spanned by the analyte-free calibration spectra, andnormalizing the result to produce a unit response. Further descriptionof embodiments of HLA techniques may be found in, for example,“Measurement of Analytes in Human Serum and Whole Blood Samples byNear-Infrared Raman Spectroscopy,” Chapter 4, Andrew J. Berger, Ph. D.thesis, Massachusetts Institute of Technology, 1998, and “An EnhancedAlgorithm for Linear Multivariate Calibration,” by Andrew J. Berger, etal., Analytical Chemistry, Vol. 70, No. 3, Feb. 1, 1998, pp. 623-627,the entirety of each of which is hereby incorporated by referenceherein. In other embodiments, the calibration coefficients may becalculated using other techniques including, for example, regressiontechniques such as, for example, ordinary least squares (OLS), partialleast squares (PLS), and/or principal component analysis.

In block 2365, the processor 416 determines whether additionalinterferent subsets ξ remain in the list of possible interferentsubsets. If another subset is present in the list, the acts in blocks2310-2360 are repeated for the next subset of interferents usingdifferent random concentrations. In some embodiments, blocks 2310-2360are performed for only the most probable subset on the list.

The calibration coefficient determined in block 2360 corresponds to asingle interferent subset ξ from the list of possible interferentsubsets and is denoted herein as a single-interferent-subset calibrationcoefficient κ_(avg)(ξ). In this example method, after all subsets ξ havebeen processed, the method continues in block 2370, in which thesingle-interferent-subset calibration coefficient is applied to themeasured spectra C_(s) to determine an estimated,single-interferent-subset analyte concentration, g(ξ)=κ_(avg)(ξ)·C_(s),for the interferent subset ξ. The set of the estimated,single-interferent-subset analyte concentrations g(ξ) for all subsets inthe list may be assembled into an array of single-interferent-subsetconcentrations. As noted above, in some embodiments the blocks 2310-2370are performed once for the most probable single-interferent-subset onthe list (e.g., the array of single-interferent analyte concentrationshas a single member).

Returning to block 2140 of FIG. 21, the array ofsingle-interferent-subset concentrations, g(ξ), is combined to determinean estimated analyte concentration, g_(est), for the material sample. Incertain embodiments, a weighting function p(ξ) is determined for each ofthe interferent subsets ξ on the list of possible interferent subsets.The weighting functions may be normalized such that Σp(ξ)=1, where thesum is over all subsets ξ that have been processed from the list ofpossible interferent subsets. In some embodiments, the weightingfunctions can be related to the minimum Mahalanobis distance or anoptimal concentration. In certain embodiments, the weighting functionp(ξ), for each subset ξ, is selected to be a constant, e.g., 1/N_(S)where N_(S) is the number of subsets processed from the list of possibleinterferent subsets. In other embodiments, other weighting functionsp(ξ) can be selected.

In certain embodiments, the estimated analyte concentration, g_(est), isdetermined (in block 2140) by combining the single-interferent-subsetestimates, g(ξ), and the weighting functions, p(ξ), to generate anaverage analyte concentration. The average concentration may be computedaccording to g_(est)=Σg(ξ) p(ξ), where the sum is over the interferentsubsets processed from the list of possible interferent subsets. In someembodiments, the weighting function p(ξ) is a constant value for eachsubset (e.g., a standard arithmetic average is used for determiningaverage analyte concentration). By testing the above described examplemethod on simulated data, it has been found that the average analyteconcentration advantageously has errors that may be reduced incomparison to other methods (e.g., methods using only a single mostprobable interferent).

Although the flowchart in FIG. 21 schematically illustrates anembodiment of the method 2100 performed with reference to the blocks2110-2140 described herein, in other embodiments, the method 2100 can beperformed differently. For example, some or all of the blocks 2110-2140can be combined, performed in a different order than shown, and/or thefunctions of particular blocks may be reallocated to other blocks and/orto different blocks. Embodiments of the method 2100 may utilizedifferent blocks than are shown in FIG. 21.

For example, in some embodiments of the method 2100, the calibrationcoefficient is computed without synthesizing spectra and/or partitioningthe data into calibration sets and test sets. Such embodiments arereferred to herein as “Parameter-Free Interferent Rejection” (PFIR)methods. In one example embodiment using PFIR, for each of the possibleinterferent subsets ξ, the following calculations may be performed tocompute an estimate of a calibration coefficient for each subset ξ. Anaverage concentration may be estimated according to g_(est)=Σg(ξ) p(ξ),where the sum is over the interferent subsets processed from the list ofpossible interferent subsets.

An example of an alternative embodiment of block 2130 includes thefollowing steps and calculations.

Step 1: For a subset's N_(IF) interferents, form a scaled interferentspectra matrix. In certain embodiments, the scaled interferent spectramatrix is the product of an interferent spectral matrix, IF, multipliedby an interferent concentration matrix, T_(max), and can be written as:IF T_(max). In certain such embodiments, the interferent concentrationmatrix T_(max) is a diagonal matrix having entries given by the maximumplasma concentrations for the various interferents.

Step 2: Calculate a covariance for the interferent component. If Xdenotes the IESD, the covariance of X, cov(X), is defined as theexpectation E((X−mean(X))(X−mean(X))^(T)) and iscov(X)≈XX^(T)/(N−1)−mean(X)mean(X)^(T).As described above, the IESD (e.g., X) is obtained as a combination ofSample Population Spectra, C, with Combination Interferent Spectra(CIS): X_(j)=C_(j)+IF_(j)ξ_(j), therefore the covariance is:cov(X)≈CC^(T)/(N−1)+IFΞΞ^(T)IF^(T)/(N−1)−mean(X)mean(X)^(T),which can be written as,cov(X)≈cov(C)+IFcov(Ξ)IF^(T).If the weights in the weighting matrix Ξ are independent and identicallydistributed, the covariance of Ξ, cov(Ξ), is a diagonal matrix havingalong the diagonal the variance, v, of the samples in Ξ. The lastequation may be written ascov(X)≈V₀+vΦ,where V₀ is the covariance of the original sample population and φ isthe covariance of the IF spectral set.

Step 3: The group's covariance may be at least partially corrected forthe presence of a single replicate of the Sample Population spectra withthe IESD as formed from N_(IF) replicates of the Sample PopulationSpectra with Combined Interferent Spectra. This partial correction maybe achieved by multiplying the second term in the covariance formulagiven above by a correction factor ρ:V=V ₀ +ρvΦ,where ρ is a scalar weighting function that depends on the number ofinterferents in the group. In some embodiments, the scalar weightingfunction is ρ=N_(IF)/(N_(IF)+1). In certain embodiments, the variance vof the weights is assumed to be the variance of a log-normal randomvariable having a 95th percentile at a value of 1.0, and a standarddeviation equal to half of the mean value.

Step 4: The eigenvectors and the corresponding eigenvalues of thecovariance matrix V are determined using any suitable linear algebraicmethods. The number of eigenvectors (and eigenvalues) is equal to thenumber of wavelengths L in the spectral measurements. The eigenvectorsmay be sorted based on decreasing order of their correspondingeigenvalues.

Step 5: The matrix of eigenvectors is decomposed so as to provide anorthogonal matrix Q. For example, in some embodiments, aQR-decomposition is performed, thereby yielding the matrix Q havingorthonormal columns and rows.

Step 6: The following matrix operations are performed on the orthogonalmatrix Q. For n=2 to L−1, the product P^(∥) _(n)=Q(:,1:n) Q(:,1:n)^(T)is calculated, where Q(:,1:n) denotes the submatrix comprising the firstn columns of the full matrix Q. The orthogonal projection, P^(⊥) _(n),away from the space spanned by Q(:,1:n) is determined by subtractingP^(∥) _(n) from the L×L identity matrix I. The n^(th) calibration vectoris then determined from κ_(n)=P¹⁹⁵ _(n)α_(X)/α_(X) ^(T)P^(⊥) _(n) α_(X),and the n^(th) error variance E_(n) is determined as the projection ofthe full covariance V onto the subspace spanned by κ_(n) as follows:E_(n)=κ_(n) ^(T)Vκ_(n).

The steps 4-6 of this example are an embodiment of the HLA technique.

In some embodiments, the calibration coefficient κ is selected as thecalibration vector corresponding to the minimum error variance E_(n).Thus, for example, the average group calibration coefficient κ may befound by searching among all the error variances for the error varianceE_(n) that has the minimum value. The calibration coefficient is thenselected as the n^(th) calibration vector κ_(n) corresponding to theminimum error variance E_(n). In other embodiments, the calibrationcoefficient is determined by averaging some or all of the calibrationvectors κ_(n).

Examples of Algorithm Results and Effects of Sample Population

Embodiments of the above-described methods have been used to estimateblood plasma glucose concentrations in humans. Four example experimentswill now be described. The population of individuals from whom sampleswere obtained for analysis (estimation of glucose concentration) will bereferred to as the “target population.” Infrared spectra obtained fromthe target population will be referred to as the “target spectra.” Inthe four example experiments, the target population included 41intensive care unit (ICU) patients. Fifty-five samples were obtainedfrom the target population.

Example Experiment 1

In this example experiment, a partial least squares (PLS) regressionmethod was applied to the infrared target spectra of the targetpatients' blood plasma to obtain the glucose estimates. In exampleexperiment 1, estimated glucose concentration was not corrected foreffects of interferents. The Sample Population used for the analysisincluded infrared spectra and independently measured glucoseconcentrations for 92 individuals selected from the general population.This Sample Population will be referred to as a “Normal Population.”

FIG. 23A plots predicted versus measured glucose measurements for 55measurements taken from 41 intensive care unit (ICU) patients. PLSregression method was applied to the infrared spectra of the patients'blood plasma to obtain the glucose measurements. In the example depictedin FIG. 23A, the Sample Population measurements include infrared spectrameasurements and independently measured glucose concentrations for 92individuals selected from the general population. This Sample Populationis referred to herein, without limitation, as a “Normal Population.”Some embodiments of a method can calculate the calibration constantsthat correspond to the infrared spectra of the Normal Population toobtain the predicted value of the glucose concentration. The populationwhose infrared spectra are intended to be analyzed by the analysisdevice and whose glucose concentration is intended to be predictedtherefrom will be referred to herein as a “target population.” Theinfrared spectra of that target population is referred to herein as the“target spectra”.

From FIG. 23A it is observed that the estimated glucose values in theblood plasma of ICU patients do not always correspond to the measuredglucose values. If the estimated glucose values matched the measuredglucose values then all the dots would lie on the straight line 2380.The estimated or predicted glucose values have an average predictionerror of 126 mg/dl and a standard deviation of prediction error of 164mg/dl. Possible reasons for the high average prediction error and highstandard deviation of prediction error could be a result of using aSample Population that includes only the Normal Population and the factthat the predicted values were not corrected for possible interferents.

Example Experiment 2

In example experiment 2, an embodiment of the Parameter-Free InterferentRejection (PFIR) method was used to estimate glucose concentration forthe same target population of patients in example experiment 1. Toachieve better correlation between the predicted glucose value and themeasured glucose value, a PFIR method can be applied to infrared spectraof the patient's blood plasma and the prediction can be corrected forinterfering substances (e.g., those present in a library ofinterferents). FIG. 23B plots the predicted versus independentlymeasured glucose values for the same patients as those of FIG. 23A,except that this time, the predicted glucose values are obtained using aPFIR method, and the prediction is corrected for interfering substances.The Sample Population was the Normal Population. In this example,calibration for Library Interferents was applied to the measured targetspectra. The Library of Interferents included spectra of the 59substances listed below:

Acetylsalicylic Acid Hetastarch Pyruvate Sodium Ampicillin Human AlbuminPyruvic Acid Sulbactam Azithromycin Hydroxy Butyric Acid SalicylateSodium Aztreonam Imipenem Cilastatin Sodium Acetate Bacitracin IohexolSodium Bicarbonate Benzyl Alcohol L_Arginine Sodium Chloride CalciumChloride Lactate Sodium Sodium Citrate Calcium Gluconate MagnesiumSulfate Sodium Thiosulfate Cefazolin Maltose Sulfadiazine CefoparazoneMannitol Urea Cefotaxime Sodium Meropenem Uric Acid Ceftazidime OxylatePotassium Voriconazole Ceftriaxone Phenytoin Xylitol D_SorbitolPhosphates Potassium Xylose Dextran Piperacillin PC 1 of Salinecovariance Ertapenem Piperacillin PC 2 of Saline covariance TazobactamEthanol PlasmaLyteA PC 3 of Saline covariance Ethosuximide Procaine HClPC 4 of Saline covariance Glycerol Propylene Glycol ICU/Normaldifference spectrum Heparin Pyrazinamide

In some embodiments, the calibration data set is determined according totwo criteria: the calibration method itself (e.g., HLA, PLS, OLS, PFIR)and the intended application of the method. The calibration data set maycomprise spectra and corresponding analyte levels derived from a set ofplasma samples from the Sample Population. In some embodiments, e.g.,those where an HLA calibration method is used, the calibration data setmay also include spectra of the analyte of interest.

From FIG. 23B it is observed that by including the spectral effects ofthe interferents in the above table, the predicted glucose values arecloser to the measured glucose values. The average prediction error inthis case is approximately −6.8 mg/dL and the standard deviation of theprediction error is approximately 23.2 mg/dL. The difference in theaverage prediction error and the standard deviation of prediction errorbetween FIG. 23A and FIG. 23B illustrates that the prediction is greatlyimproved when the model includes the effects of possible interferents.

In the example experiments 1 and 2, the Sample Population was the NormalPopulation. Thus, samples were drawn from a population of normalindividuals who did not have identifiable medical conditions that mightaffect the spectra of their plasma samples. For example, the sampleplasma spectra typically did not show effects of high levels ofmedications or other substances (e.g., ethanol), or effects of chemicalsthat are indicative of kidney or liver malfunction. Similarly, in thedata presented in FIGS. 23A and 23B, the Sample Population samples aredrawn from a population of normal individuals. These individuals do nothave identifiable medical conditions that might affect the spectra oftheir plasma, for example, the spectra of their plasma may not exhibithigh plasma levels of medications or other substances such as ethanol,or other chemicals that are indicative of kidney or liver malfunction.

In some embodiments, an analysis method may calibrate for deviationsfrom the distribution defined by the calibration plasma spectra byidentifying a “base” set of interferent spectra likely to be responsiblefor the deviation. The analysis method may then recalibrate with respectto an enhanced spectral data set. In some embodiments, the enhancementcan be achieved by including the identified interferent spectra into thecalibration plasma spectra. When it is anticipated that the targetpopulation may have been administered significant amounts of substancesnot present in the samples of the calibration set, or when the targetpopulation have many distinct interferents, estimation of theinterferents present in the target spectrum may be subject to a largedegree of uncertainty. In some cases, this may cause analyte estimationto be subject to errors.

Accordingly, in certain embodiments, the calibration data set may beenhanced beyond the base of “normal” samples to include a population ofsamples intended to be more representative of the target population. Theenhancement of the calibration set may be generated, in someembodiments, by including samples from a sufficiently diverse range ofindividuals in order to represent the range of likely interferents (bothin type and in concentration) and/or the normal variability inunderlying plasma characteristics. The enhancement may, additionally oralternatively, be generated by synthesizing interferent spectra having arange of concentrations as described above (see, e.g., discussion ofblock 2310 in FIG. 23). Using the enhanced calibration set may reducethe error in estimating the analyte concentration in the target spectra.

Example Experiments 3 and 4

Example experiments 3 and 4 use the analysis methods of exampleexperiments 1 and 2, respectively (PLS without interferent correctionand PFIR with interferent correction). However, example experiments 3and 4 use a Sample Population having blood plasma spectralcharacteristics different from the Normal Population used in exampleexperiments 1 and 2. In example experiments 3 and 4, the SamplePopulation was modified to include spectra of both the Normal Populationand spectra of an additional population of 55 ICU patients. Thesespectra will be referred to as the “Normal+Target Spectra.” Inexperiments 3 and 4, the ICU patients included Surgical ICU patients,Medical ICU patients as well as victims of severe trauma, including alarge proportion of patients who had suffered major blood loss. Majorblood loss may necessitate replacement of the patient's total bloodvolume multiple times during a single day and subsequent treatment ofthe patient via electrolyte and/or fluid replacement therapies. Majorblood loss may also require administration of plasma-expandingmedications. Major blood loss may lead to significant deviations fromthe blood plasma spectra representative of a Normal Population. Thepopulation of 55 ICU patients (who provided the Target Spectra) has somesimilarities to the individuals for whom the analyses in experiments 1-4were performed (e.g., all were ICU patients), but in these experiments,target spectra from individuals in the target population were notincluded in the Target Spectra.

FIG. 23C and FIG. 23D illustrate the principles discussed with respectto Experiments 3 and 4. Specifically, to obtain the data presented inFIG. 23C, the method used to obtain the data of FIG. 23A is modified toinclude spectra of both Normal Population members and spectra of 55 ICUpatients. (The target population, for such a method, can advantageouslycomprise ICU patients. For example, the spectra obtained from a targetpopulation of ICU patients can be similar in many ways to the spectraobtained from the 55 ICU patients.) This combined set of Spectra isreferred to herein as the “Normal+Target Spectra.” In this particularstudy, the ICU was a major trauma center, and the ICU patients were allvictims of severe trauma, including a large proportion of patients whohad suffered major blood loss. In such cases, researchers generallyagree that this degree of blood loss—which may necessitate replacementof the patient's total blood volume multiple times during a single dayand subsequent treatment of the patient via electrolyte/fluidreplacement and the administration of plasma-expanding medications—canlead to significant spectral deviations from the blood plasma spectra ofa Normal Population. A comparison of FIG. 23A and FIG. 23C shows thatthe predicted glucose values match the measured glucose values to agreater extent in FIG. 23C than in FIG. 23A. Statistical analysis of thedata presented in FIG. 23C shows that the average prediction error ofthe predicted glucose value is approximately 8.2 mg/dl and the standarddeviation of the prediction error is approximately 16.9 mg/dl. It shouldbe noted that in predicting the glucose value in FIG. 23C, the presenceof interferents was not taken into account.

The data shown in FIG. 23D, is obtained by modifying the method used toobtain the data for FIG. 23B (which included correction for possibleinterferents) to include spectra of the “Normal+Target Spectra.” Acomparison of FIG. 23B and FIG. 23D shows that the predicted glucosevalues match the measured glucose values to a greater extent in FIG. 23Dthan in FIG. 23B. Statistical analysis of the data presented in FIG. 23Dshows that in this example, the average prediction error of thepredicted glucose value is approximately 1.32 mg/dl and the standarddeviation of the prediction error is approximately 12.6 mg/dl. It can beconcluded from this example that determining calibration constants froma population that includes both normal spectra and spectra derived fromindividuals similar to those of the target population, and alsocorrecting for possible interferents, provides a good match between theestimated value and the measured value.

Results of example experiments 1-4 are shown in the following table. Theglucose concentrations estimated from the analysis method were comparedto independently determined glucose measurements to provide an averageprediction error and a standard deviation of the average predictionerror. The table demonstrates that independent of the Sample Populationused (e.g., either the Normal Population or the Normal+TargetPopulation), calibrating for interferents reduces both the averageprediction error and the standard deviation (e.g., compare the resultsfor experiment 2 to the results for experiment 1 and compare the resultsfor experiment 4 to the results for experiment 3). The table furtherdemonstrates that independent of the analysis method used (e.g., eitherPLS or PFIR), using a Sample Population with more similarity to thetarget population (e.g., the Normal+Target Population) reduces both theaverage prediction error and the standard deviation (e.g., compare theresults for experiment 3 to the results for experiment 1 and compare theresults for experiment 4 to the results for experiment 2).

Average Example Prediction Standard Experiment Interferent Sample ErrorDeviation No. Calibration Population (mg/dL) (mg/dL) 1 NO Normal 126 1642 YES Normal −6.8 23.2 3 NO Normal + Target 8.2 16.9 4 YES Normal +Target 1.32 12.6

Accordingly, embodiments of analysis methods that use a SamplePopulation that includes both normal spectra and spectra fromindividuals similar to those of the target population and that calibratefor possible interferents provide a good match between the estimatedglucose concentration and the measured glucose concentration. Asdiscussed above, a suitable Sample Population may be assembled from thePopulation Database in order to include normal spectra plus suitabletarget spectra from individuals that match a desired target populationincluding, for example, ICU patients, trauma patients, a particulardemographic group, a group having a common medical condition (e.g.,diabetes), and so forth.

User Interface

The system 400 can include a display system 414, for example, asdepicted in FIG. 4. The display system 414 may comprise an input deviceincluding, for example, a keypad or a keyboard, a mouse, a touchscreendisplay, and/or any other suitable device for inputting commands and/orinformation. The display system 414 may also include an output deviceincluding, for example, an LCD monitor, a CRT monitor, a touchscreendisplay, a printer, and/or any other suitable device for outputtingtext, graphics, images, videos, etc. In some embodiments, a touchscreendisplay is advantageously used for both input and output.

The display system 414 can include a user interface 2400 by which userscan conveniently and efficiently interact with the system 400. The userinterface 2400 may be displayed on the output device of the system 400(e.g., the touchscreen display). In some embodiments, the user interface2400 is implemented and/or stored as one or more code modules, which maybe embodied in hardware, firmware, and/or software.

FIGS. 24 and 25 schematically illustrate the visual appearance ofembodiments of the user interface 2400. The user interface 2400 may showpatient identification information 2402, which can include patient nameand/or a patient ID number. The user interface 2400 also can include thecurrent date and time 2404. An operating graphic 2406 shows theoperating status of the system 400. For example, as shown in FIGS. 24and 25, the operating status is “Running,” which indicates that thesystem 400 is fluidly connected to the patient (“Jill Doe”) andperforming normal system functions such as infusing fluid and/or drawingblood. The user interface 2400 can include one or more analyteconcentration graphics 2408, 2412, which may show the name of theanalyte and its last measured concentration. For example, the graphic2408 in FIG. 24 shows “Glucose” concentration of 150 mg/dL, while thegraphic 2412 shows “Lactate” concentration of 0.5 mmol/L. The particularanalytes displayed and their measurement units (e.g., mg/dL, mmol/L, orother suitable unit) may be selected by the user. The size of thegraphics 2408, 2412 may be selected to be easily readable out to adistance such as, e.g., 30 feet. The user interface 2400 may alsoinclude a next-reading graphic 2410 that indicates the time until thenext analyte measurement is to be taken. In FIG. 24, the time until nextreading is 3 minutes, whereas in FIG. 25, the time is 6 minutes, 13seconds.

The user interface 2400 can include an analyte concentration statusgraphic 2414 that indicates status of the patient's current analyteconcentration compared with a reference standard. For example, theanalyte may be glucose, and the reference standard may be a hospitalICU's tight glycemic control (TGC). In FIG. 24, the status graphic 2414displays “High Glucose,” because the glucose concentration (150 mg/dL)exceeds the maximum value of the reference standard. In FIG. 25, thestatus graphic 2414 displays “Low Glucose,” because the current glucoseconcentration (79 mg/dL) is below the minimum reference standard. If theanalyte concentration is within bounds of the reference standard, thestatus graphic 2414 may indicate normal (e.g., “Normal Glucose”), or itmay not be displayed at all. The status graphic 2414 may have abackground color (e.g., red) when the analyte concentration exceeds theacceptable bounds of the reference standard.

The user interface 2400 can include one or more trend indicators 2416that provide a graphic indicating the time history of the concentrationof an analyte of interest. In FIGS. 24 and 25, the trend indicator 2416comprises a graph of the glucose concentration (in mg/dL) versus elapsedtime (in hours) since the measurements started. The graph includes atrend line 2418 indicating the time-dependent glucose concentration. Inother embodiments, the trend line 2418 can include measurement errorbars and may be displayed as a series of individual data points. In FIG.25, the glucose trend indicator 2416 is shown as well as a trendindicator 2430 and trend line 2432 for the lactate concentration. Insome embodiments, a user may select whether none, one, or both trendindicators 2416, 2418 are displayed. In some embodiments, one or both ofthe trend indicators 2416, 2418 may appear only when the correspondinganalyte is in a range of interest such as, for example, above or belowthe bounds of a reference standard.

The user interface 2400 can include one or more buttons 2420-2426 thatcan be actuated by a user to provide additional functionality or tobring up suitable context-sensitive menus and/or screens. For example,in the embodiments shown in FIG. 24 and FIG. 25, four buttons 2420-2426are shown, although fewer or more buttons are used in other embodiments.The button 2420 (“End Monitoring”) may be pressed when one or moreremovable portions (see, e.g., 710 of FIG. 7) are to be removed. In manyembodiments, because the removable portions 710, 712 are not reusable, aconfirmation window appears when the button 2420 is pressed. If the useris certain that monitoring should stop, the user can confirm this byactuating an affirmative button in the confirmation window. If thebutton 2420 were pushed by mistake, the user can select a negativebutton in the confirmation window. If “End Monitoring” is confirmed, thesystem 400 performs appropriate actions to cease fluid infusion andblood draw and to permit ejection of a removable portion (e.g., theremovable portion 710).

The button 2422 (“Pause”) may be actuated by the user if patientmonitoring is to be interrupted but is not intended to end. For example,the “Pause” button 2422 may be actuated if the patient is to betemporarily disconnected from the system 400 (e.g., by disconnecting thetubes 306). After the patient is reconnected, the button 2422 may bepressed again to resume monitoring. In some embodiments, after the“Pause” button 2422 has been pressed, the button 2422 displays “Resume.”

The button 2424 (“Delay 5 Minutes”) causes the system 400 to delay thenext measurement by a delay time period (e.g., 5 minutes in the depictedembodiments). Actuating the delay button 2424 may be advantageous iftaking a reading would be temporarily inconvenient, for example, becausea health care professional is attending to other needs of the patient.The delay button 2424 may be pressed repeatedly to provide longerdelays. In some embodiments, pressing the delay button 2424 isineffective if the accumulated delay exceeds a maximum threshold. Thenext-reading graphic 2410 automatically increases the displayed timeuntil the next reading for every actuation of the delay button 2424 (upto the maximum delay).

The button 2426 (“Dose History”) may be actuated to bring up a dosinghistory window that displays patient dosing history for an analyte ormedicament of interest. For example, in some embodiments, the dosinghistory window displays insulin dosing history of the patient and/orappropriate hospital dosing protocols. A nurse attending the patient canactuate the dosing history button 2426 to determine the time when thepatient last received an insulin dose, the last dose amount, and/or thetime and amount of the next dose. The system 400 may receive the patientdosing history via wired or wireless communications from a hospitalinformation system.

In other embodiments, the user interface 2400 can include additionaland/or different buttons, menus, screens, graphics, etc. that are usedto implement additional and/or different functionalities.

Related Components

FIG. 26 schematically depicts various components and/or aspects of apatient monitoring system 2630 and how those components and/or aspectsrelate to each other. In some embodiments, the monitoring system 2630can be the apparatus 100 for withdrawing and analyzing fluid samples.Some of the depicted components can be included in a kit containing aplurality of components. Some of the depicted components, including, forexample, the components represented within the dashed rounded rectangle2640 of FIG. 26, are optional and/or can be sold separately from othercomponents.

The patient monitoring system 2630 shown in FIG. 26 includes amonitoring apparatus 2632. The monitoring apparatus 2632 can be themonitoring device 102, shown in FIG. 1 and/or the system 400 of FIG. 4.The monitoring apparatus 2632 can provide monitoring of physiologicalparameters of a patient. In some embodiments, the monitoring apparatus2632 measures glucose and/or lactate concentrations in the patient'sblood. In some embodiments, the measurement of such physiologicalparameters is substantially continuous. The monitoring apparatus 2632may also measure other physiological parameters of the patient. In someembodiments, the monitoring apparatus 2632 is used in an intensive careunit (ICU) environment. In some embodiments, one monitoring apparatus2632 is allocated to each patient room in an ICU.

The patient monitoring system 2630 can include an optional interfacecable 2642. In some embodiments, the interface cable 2642 connects themonitoring apparatus 2632 to a patient monitor (not shown). Theinterface cable 2642 can be used to transfer data from the monitoringapparatus 2632 to the patient monitor for display. In some embodiments,the patient monitor is a bedside cardiac monitor having a display thatis located in the patient room (see, e.g., the user interface 2400 shownin FIG. 24 and FIG. 25.) In some embodiments, the interface cable 2642transfers data from the monitoring apparatus 2632 to a central stationmonitor and/or to a hospital information system (HIS). The ability totransfer data to a central station monitor and/or to a HIS may depend onthe capabilities of the patient monitor system.

In the embodiment shown in FIG. 26, an optional bar code scanner 2644 isconnected to the monitoring apparatus 2632. In some embodiments, the barcode scanner 2644 is used to enter patient identification codes, nurseidentification codes, and/or other identifiers into the monitoringapparatus 2632. In some embodiments, the bar code scanner 2644 containsno moving parts. The bar code scanner 2644 can be operated by manuallysweeping the scanner 2644 across a printed bar code or by any othersuitable means. In some embodiments, the bar code scanner 2644 includesan elongated housing in the shape of a wand.

The patient monitoring system 2630 includes a fluid system kit 2634connected to the monitoring apparatus 2632. In some embodiments, thefluid system kit 2634 includes fluidic tubes that connect a fluid sourceto an analytic subsystem. For example, the fluidic tubes can facilitatefluid communication between a blood source or a saline source and anassembly including a sample holder and/or a centrifuge. In someembodiments, the fluid system kit 2634 includes many of the componentsthat enable operation of the monitoring apparatus 2632. In someembodiments, the fluid system kit 2634 can be used with anti-clottingagents (such as heparin), saline, a saline infusion set, a patientcatheter, a port sharing IV infusion pump, and/or an infusion set for anIV infusion pump, any or all of which may be made by a variety ofmanufacturers. In some embodiments, the fluid system kit 2634 includes amonolithic housing that is sterile and disposable. In some embodiments,at least a portion of the fluid system kit 2634 is designed for singlepatient use. For example, the fluid system kit 2634 can be constructedsuch that it can be economically discarded and replaced with a new fluidsystem kit 2634 for every new patient to which the patient monitoringsystem 2630 is connected. In addition, at least a portion of the fluidsystem kit 2634 can be designed to be discarded after a certain periodof use, such as a day, several days, several hours, three days, acombination of hours and days such as, for example, three days and twohours, or some other period of time. Limiting the period of use of thefluid system kit 2634 may decrease the risk of malfunction, infection,or other conditions that can result from use of a medical apparatus foran extended period of time.

In some embodiments, the fluid system kit 2634 includes a connector witha luer fitting for connection to a saline source. The connector may be,for example, a three-inch pigtail connector. In some embodiments, thefluid system kit 2634 can be used with a variety of spikes and/or IVsets used to connect to a saline bag. In some embodiments, the fluidsystem kit 2634 also includes a three-inch pigtail connector with a luerfitting for connection to one or more IV pumps. In some embodiments, thefluid system kit 2634 can be used with one or more IV sets made by avariety of manufacturers, including IV sets obtained by a user of thefluid system kit 2634 for use with an infusion pump. In someembodiments, the fluid system kit 2634 includes a tube with a low deadvolume luer connector for attachment to a patient vascular access point.For example, the tube can be approximately seven feet in length and canbe configured to connect to a proximal port of a cardiovascularcatheter. In some embodiments, the fluid system kit 2634 can be usedwith a variety of cardiovascular catheters, which can be supplied, forexample, by a user of the fluid system kit 2634.

As shown in FIG. 26, the monitoring apparatus 2632 is connected to asupport apparatus 2636, such as an IV pole. The support apparatus 2636can be customized for use with the monitoring apparatus 2632. A vendorof the monitoring apparatus 2632 may choose to bundle the monitoringapparatus 2632 with a custom support apparatus 2636. In someembodiments, the support apparatus 2636 includes a mounting platform forthe monitoring apparatus 2632. The mounting platform can include mountsthat are adapted to engage threaded inserts in the monitoring apparatus2632. The support apparatus 2636 can also include one or morecylindrical sections having a diameter of a standard IV pole, forexample, so that other medical devices, such as IV pumps, can be mountedto the support apparatus. The support apparatus 2636 can also include aclamp adapted to secure the apparatus to a hospital bed, an ICU bed, oranother variety of patient conveyance device.

In the embodiment shown in FIG. 26, the monitoring apparatus 2632 iselectrically connected to an optional computer system 2646. The computersystem 2646 can comprise one or multiple computers, and it can be usedto communicate with one or more monitoring devices. In an ICUenvironment, the computer system 2646 can be connected to at least someof the monitoring devices in the ICU. The computer system 2646 can beused to control configurations and settings for multiple monitoringdevices (for example, the system can be used to keep configurations andsettings of a group of monitoring devices common). The computer system2646 can also run optional software, such as data analysis software2648, HIS interface software 2650, and insulin dosing software 2652.

In some embodiments, the computer system 2646 runs optional dataanalysis software 2648 that organizes and presents information obtainedfrom one or more monitoring devices. In some embodiments, the dataanalysis software 2648 collects and analyzes data from the monitoringdevices in an ICU. The data analysis software 2648 can also presentcharts, graphs, and statistics to a user of the computer system 2646.

In some embodiments, the computer system 2646 runs optional hospitalinformation system (HIS) interface software 2650 that provides aninterface point between one or more monitoring devices and an HIS. TheHIS interface software 2650 may also be capable of communicating databetween one or more monitoring devices and a laboratory informationsystem (LIS).

In some embodiments, the computer system 2646 runs optional insulindosing software 2652 that provides a platform for implementation of aninsulin dosing regimen. In some embodiments, the hospital tight glycemiccontrol protocol is included in the software. The protocol allowscomputation of proper insulin doses for a patient connected to amonitoring device 2646. The insulin dosing software 2652 can communicatewith the monitoring device 2646 to ensure (or at least improve thelikelihood) that proper insulin doses are calculated. For example, theinsulin dosing software 2652 can communicate with the computer system2646 to perform the dosing calculations. The user interface 2400 can beused to communicate relevant information such as, for example, rate ofdose and/or infusion, type of dose and/or infusion (e.g., bolusinjection, basal infusion, steady state dose, treatment dose, etc.), toa health care practitioner so that the infusion rate and type of dosecan be provided to the patient. The insulin dosing software 2652 anduser interface can be implemented with the monitoring system 102 (FIG.1), the system 400 (FIG. 4), or any other suitable patient monitoringsystem.

Analyte Control And Monitoring

In some embodiments, it can be advantageous to control a level of ananalyte (e.g., glucose) in a patient using an embodiment of an analytedetection system described herein. Although certain examples of glucosecontrol are described below, embodiments of the systems and methodsdisclosed herein can be used to monitor and/or control other analytes(e.g., lactate).

For example, diabetic individuals control their glucose levels byadministration of insulin. If a diabetic patient is admitted to ahospital or ICU, the patient may be in a condition in which he or shecannot self-administer insulin. Advantageously, embodiments of theanalyte detection systems disclosed herein can be used to control thelevel of glucose in the patient. Additionally, it has been found that amajority of patients admitted to the ICU exhibit hyperglycemia withouthaving diabetes. In such patients it may be beneficial to monitor andcontrol their blood glucose level to be within a particular range ofvalues. Further, it has been shown that tightly controlling bloodglucose levels to be within a stringent range may be beneficial topatients undergoing surgical procedures.

A patient admitted to the ICU or undergoing surgery can be administereda variety of drugs and fluids such as Hetastarch, intravenousantibiotics, intravenous glucose, intravenous insulin, intravenousfluids such as saline, etc., which may act as interferents and make itdifficult to determine the blood glucose level. Moreover, the presenceof additional drugs and fluids in the blood stream may require differentmethods for measuring and controlling blood glucose level. Also, thepatient may exhibit significant changes in hematocrit levels due toblood loss or internal hemorrhage, and there can be unexpected changesin the blood gas level or a rise in the level of bilirubin and ammonialevels in the event of an organ failure. Embodiments of the systems andmethods disclosed herein advantageously can be used to monitor andcontrol blood glucose (and/or other analytes) in the presence ofpossible interferents to estimation of glucose and for patientsexperiencing health problems.

In some environments, Tight Glycemic Control (TGC) can include: (1)substantially continuous monitoring (which can include periodicmonitoring, at relatively frequent intervals of every 15, 30, 45, and/or60 minutes, for example) of glucose levels; (2) determination ofsubstances that tend to increase glucose levels (e.g., sugars such asdextrose) and/or decrease glucose levels (e.g., insulin); and/or (3)responsive delivery of one or more of such substances, if appropriateunder the controlling TGC protocol. For example, one possible TGCprotocol can be achieved by controlling glucose within a relativelynarrow range (for example between 70 mg/dL to 110 mg/dL). As will befurther described, in some embodiments, TGC can be achieved by using ananalyte monitoring system to make continuous and/or periodic butfrequent measurements of glucose levels.

In some embodiments, the analyte detection system schematicallyillustrated in FIGS. 4, 5, and 6 can be used to regulate theconcentration of one or more analytes in the sample in addition todetermining and monitoring the concentration of the one or moreanalytes. In some cases, the analyte detection system can be used in anICU to monitor (and/or control) analytes that may be present in patientsexperiencing trauma. In some implementations, the concentration of theanalytes is regulated to be within a certain range. The range can bepredetermined (e.g., according to a hospital protocol or a physician'srecommendation), or the range can be adjusted as conditions change.

In an example of glycemic control, a system can be used to determine andmonitor the concentration of glucose in the sample. If the concentrationof glucose falls below a lower threshold, glucose from an externalsource can be supplied and/or delivery of insulin can be scaled back orhalted altogether. If the concentration of glucose exceeds an upperthreshold, insulin from an external source can be supplied and/ordelivery of glucose can be scaled back or halted altogether. A treatmentdose of glucose and/or insulin can be infused into a patientcontinuously over a certain time interval or can be injected in arelatively large quantity at once (referred to as “bolus injection”).Moreover, a steady-state or baseline (as opposed to a treatment) can beachieved as glucose and/or insulin can be infused into a patientrelatively continuously at a low delivery rate (referred to as “basalinfusion”) to maintain the concentration of one or more analytes withina predetermined range. For example, in some cases a basal infusion cancomprise a series of discrete doses designed to maintain a concentrationof one or more analytes in a patient (e.g., concentration of glucose ina patient's blood stream). Such a serial infusion of discrete packets ordoses can be referred to as “pulsatile” infusion. In some cases, insteadof a series of discrete doses, a steady stream of infusion substance canbe provided. The automatic and/or recommended basal infusion rate ofglucose or insulin can be determined on the basis of one or morefactors. For example, body weight, medical condition, medical history,presence or absence of other drugs and chemicals in the patient, etc.can all be factors that contribute to such a determination. Withoutcontradicting the use of the term “basal” set forth above, the “basalinfusion rate” can also refer to the rate of insulin needed to cover the“basal” metabolic functions (e.g. breathing, maintaining heart rate andother metabolic processes).

Various dosing protocols can be used to determine a dose of a treatmentsubstance (e.g., a drug, glucose, dextrose, insulin, etc.). For example,in some embodiments, the dosing protocol used by personnel at a hospitalis integrated into the glucose monitoring system to automaticallydetermine the delivery rate of the treatment drug. In some embodiments,the system and method for recommending insulin bolus quantities to aninsulin user disclosed in U.S. Pat. No. 7,291,107 B2 titled “INSULINBOLUS RECOMMENDATION SYSTEM”, by Hellwig et. al. can be used with theabove described glucose monitoring system to determine the bolus dose ofinsulin to be delivered to the patient in the event of hyperglycemia orhypoglycemia. The entire content of U.S. Pat. No. 7,291,107 B2 is herebyincorporated by reference herein and is made a part of thisspecification.

In some embodiments, a hospital dosing protocol can be integrated into aglucose monitoring and control system. For example, the protocolinstructions for a nurse can be accomplished automatically by the systemrather than by the nurse. In some embodiments, a hospital or otherhealth care provider can use its own protocol and program a monitoringsystem to incorporate the specific protocol. The procedure outline andcorresponding tables below are an example of such a dosing protocol (theexample provided can be referred to as the “Atlanta Protocol” andrelated information publically available at the following web address:“http://www.gha.org/pha/health/diabetes/Toolkit/guidelines/IVins80110/80-110chart_co11-16.pdf”).The following protocol can also be modified and incorporated into amonitoring system:

START infusion using the drip rate (ml/hr) shown in Column 2 for thecurrent Blood Glucose Range. To determine the new drip rate for eachhourly measurement, compare the latest BG Range to the previous BG RangeIf latest BG Range has decreased: Stay in the same column If latest BGRange has not changed or increased: Move 1 column to the right Whenhourly BG 80-110, stay in the same column to determine the new driprate. (Do Not Change Columns) When BG <80, move one column to the leftand treat for hypoglycemia Blood 2 Glucose 1 (ml/hr) 3 4 5 6 7 8 9 10Ranges (ml/hr) START (ml/hr) (ml/hr) (ml/hr) (ml/hr) (ml/hr) (ml/hr)(ml/hr) (ml/hr) >450 4.4 8.8 13.2 17.6 22.0 26.4 30.8 35.2 39.6 44.0385-450 3.6 7.2 10.8 14.4 18.0 21.6 25.2 28.8 32.4 36.0 326-384 3.0 6.09.0 12.0 15.0 18.0 21.0 24.0 27.0 30.0 290-333 2.5 5.0 7.5 10.0 12.515.0 17.5 20.0 22.5 25.0 251-289 2.1 4.2 6.3 8.4 10.5 12.6 14.7 16.818.9 21.0 217-250 1.7 3.4 5.1 7.2 8.5 10.2 11.9 13.6 15.3 17.0 188-2161.4 2.8 4.2 5.6 7.0 8.4 9.8 11.2 12.6 14.0 163-187 1.2 2.4 3.6 4.8 6.07.2 8.4 9.6 10.8 12.0 141-162 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0119-140 0.8 1.6 2.4 3.2 4.0 4.8 5.6 6.4 7.2 8.0 111-120 0.6 1.2 1.8 2.43.0 3.6 4.2 4.8 5.4 6.0 106-110 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0101-105 0.4 0.9 1.3 1.8 2.2 2.7 3.1 3.6 4.0 4.5  96-100 0.4 0.8 1.2 1.62.0 2.4 2.8 3.2 3.6 4.0 91-95 0.3 0.7 1.0 1.4 1.7 2.1 2.4 2.8 3.2 3.586-90 0.3 0.6 0.9 1.2 1.5 1.8 2.1 2.4 2.7 3.0 80-85 0.2 0.5 0.7 1.0 1.21.5 1.7 2.0 2.3 2.5 75-79 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 70-740.1 0.3 0.4 0.6 0.7 0.9 1.0 1.2 1.3 1.5 60-70 0.1 0.2 0.3 0.4 0.5 0.60.7 0.8 0.9 1.0  <60 0 0 0 0 0 0 0 0 0 0 BG D50W ACTION 70-79 10.0 ml IVpush Move 1 column to the left 60-69 15.0 ml IV push Recheck BG in 15minutes Repeat as necessary 50-59 20.0 ml IV push Move 1 column to theleft 30-49 25.0 ml IV push Recheck BG in 15 minutes <30 30.0 ml IV pushRepeat as necessary Contact Physician if BG <60 for 2 consecutive BGmeasurements Notify Physician If: BG is less <60 for 2 consecutive BGmeasurements BG reverts to >200 for 2 consecutive BG measurementsInsulin requirement exceeds 24 units/hour If the K+ level drops to <4 Ifdrip rate (ml/hr) is 0.5 or less If continuous enteral feeding, TPN, orIV insulin infusion is stopped or interrupted

In some embodiments, a glycemic control system is capable of deliveringglucose, dextrose, glycogen, and/or glucagon from an external sourcerelatively quickly in the event of hypoglycemia. As discussed herein,embodiments of the glycemic control system are capable of deliveringinsulin from an external source relatively quickly in the event ofhyperglycemia.

Returning to FIGS. 5 and 6, these figures schematically illustrateembodiments of a fluid handling system that comprise optional analytecontrol subsystems 2780. The analyte control subsystem 2780 can be usedfor providing control of an analyte such as, e.g., glucose, and mayprovide delivery of the analyte and/or related substances (e.g.,dextrose solution and/or insulin in the case of glucose). The analytecontrol subsystem 2780 comprises a source 2782 such as, for example, theanalyte (or a suitable compound related to the analyte) dissolved inwater or saline. For example, if the analyte is glucose, the source 2782may comprise a bag of dextrose solution (e.g., Dextrose or Dextrose50%). The source 2782 can be coupled to an infusion pump (not shown).The source 2782 and the infusion pump can be provided separately fromthe analyte control subsystem 2780. For example, a hospitaladvantageously can use existing dextrose bags and infusion pumps withthe subsystem 2780.

As schematically illustrated in FIGS. 5 and 6, the source 2782 is influid communication with the patient tube 512 via a tube 2784 andsuitable connectors. A pinch valve 2786 can be disposed adjacent thetube 2784 to regulate the flow of fluid from the source 2782. A patientinjection port can be located at a short distance from the proximal portof the central venous catheter or some other catheter connected to thepatient.

In an example implementation for glycemic control, if the analytedetection system determines that the level of glucose has fallen below alower threshold value (e.g., the patient is hypoglycemic), a controlsystem (e.g., the fluid system controller 405 in some embodiments)controlling an infusion delivery system may close the pinch valves 521and/or 542 to prevent infusion of insulin and/or saline into thepatient. The control system may open the pinch valve 2786 and dextrosesolution from the source 2782 can be infused (or alternatively injectedas a bolus) into the patient. After a suitable amount of dextrosesolution has been infused to the patient, the pinch valve 2786 can beclosed, and the pinch valves 521 and/or 542 can be opened to allow flowof insulin and/or saline. In some systems, the amount of dextrosesolution to be delivered as a basal infusion or as a bolus injection canbe calculated based on one or more detected concentration levels ofglucose. The source 2782 advantageously can be located at a short enoughfluidic distance from the patient such that dextrose can be delivered tothe patient within a time period of about one to about ten minutes ofreceiving an instruction (e.g. from a control system or a health careprovider). In other embodiments, the source 2782 can be located at thesite where the patient tube 512 interfaces with the patient so thatdextrose can be delivered within about one minute of receiving aninstruction (e.g. from a control system or a health care provider).

If the analyte detection system determines that the level of glucose hasincreased above an upper threshold value (e.g., the patient ishyperglycemic), the control system may close the pinch valves 542 and/or2786 to prevent infusion of saline and/or dextrose into the patient. Thecontrol system may open the pinch valve 521, and insulin can be infusedat a basal infusion rate (and/or injected as a bolus) into the patient.After a suitable amount of insulin has been infused (or bolus injected)to the patient, the control system can close the pinch valve 521 andopen the pinch valves 542 and/or 2786 to allow flow of saline and/orglucose. The suitable amount of insulin can be calculated based on oneor more detected concentration levels of glucose in the patient. In someembodiments, the insulin source can be connected to the infusion pump518 which advantageously can be located at a short enough fluidicdistance from the patient such that insulin can be delivered to thepatient rapidly, e.g., within about one to about ten minutes. In someembodiments, the insulin source can be located at the site where thepatient tube 512 interfaces with the patient so that insulin can bedelivered to the patient rapidly, e.g., within about one minute.

In some embodiments, sampling bodily fluid from a patient and providingmedication to the patient can be achieved through the same lines of thefluid handling system. For example, in some embodiments, a port to apatient can be shared by alternately drawing samples and medicatingthrough the same line. In some embodiments, a insulin can be provided tothe patient at regular intervals (in the same or different lines). Forexample, insulin can be provided to a patient after meals. In someembodiments, the medication can be delivered to the patient continuouslyat a basal infusion rate combined with intermittent bolus injections(e.g. after meals). In some embodiments, the medication can be deliveredthrough a fluid passageway connected to the patient (e.g. patient tube512 of FIG. 5). Intermittent injections can be provided to the patientby the same fluid passageway (e.g. patient tube 512 of FIG. 5). In someembodiments, a separate delivery system comprising a delivery pump canbe used to provide the medication. In some embodiments comprising ashared line, medication can be delivered when returning part of a bodyfluid sample back to the patient. In some implementations, medication isdelivered midway between samples (e.g., every 7.5 minutes if samples aredrawn every 15 minutes). In some embodiments, a dual lumen tube can beused, wherein one lumen is used for the sample and the other lumen tomedicate. In some embodiments, an analyte detection system (e.g., an“OptiScanner®” monitor) may provide suitable commands to a separateinsulin pump (on a shared port or different line) to provide therecommended dose of insulin.

Example Method for Glycemic Control

FIG. 27 is a flowchart that schematically illustrates an exampleembodiment of a method 2700 of providing analyte control. The exampleembodiment is directed toward one possible implementation for glycemiccontrol (including but not limited to tight glycemic control) and isintended to illustrate certain aspects of the method 2700 and is notintended to limit the scope of possible analyte control methods. Inblock 2705, a glucose monitoring apparatus (e.g., the monitoringapparatus 2632 of FIG. 26) draws a sample (e.g., a blood or blood plasmasample) from a sample source (e.g., a patient) and obtains a measurementfrom the sample (e.g., a portion of the drawn sample). The measurementmay comprise an optical measurement such as, for example, an infraredspectrum of the sample. In block 2710, the measurement sample isanalyzed to identify possible interferents to an estimation of theglucose concentration in the measurement sample. In block 2715, a modelis generated for estimating the glucose concentration from the obtainedmeasurement. In some embodiments, models developed from the algorithmsdescribe above with reference to FIGS. 21-23 are used. The generatedmodel may reduce or minimize effects of the identified interferents onthe estimated glucose concentration, in certain embodiments. In block2720, an estimated glucose concentration is determined from the modeland the obtained measurement. In block 2725, the estimated glucoseconcentration in the sample is compared to an acceptable range ofconcentrations. The acceptable range can be determined according to asuitable glycemic control protocol such as, for example, a TGC protocol.For example, in certain TGC protocols the acceptable range can be aglucose concentration in a range from about 70 mg/dL to about 110 mg/dL.If the estimated glucose concentration lies within the acceptable range,the method 2700 returns to block 2705 to obtain the next samplemeasurement, which can be made after a relatively short or a relativelylong time period has elapsed since the last measurement. For example,the next measurement can be taken within about one minute. In anotherexample, the succeeding measurement can be taken after about one hour.In other examples, measurements are taken every fifteen minutes or less,every thirty minutes or less, ever forty-five minutes or less, etc. Insome embodiments, a treatment substance (e.g. insulin or glucose) ordrug can be continuously infused through the patient even if theestimated glucose concentration is already within the predeterminedrange. This can be advantageous when it is determined, for example, thatwithout such a basal injection, the glucose concentration may driftoutside the range, or when it is predicted that the glucoseconcentration would preferably be within another range.

In block 2725, if the estimated glucose concentration is outside theacceptable range of concentrations, then the method 2700 proceeds toblock 2740 in which the estimated glucose concentration is compared witha desired glucose concentration. The desired glucose concentration canbe based on, for example, the acceptable range of glucoseconcentrations, the parameters of the particular glycemic protocol, thepatient's estimated glucose concentration, and so forth. If theestimated glucose concentration is below the desired concentration(e.g., the patient is hypoglycemic), a dose of dextrose to be deliveredto the patient is calculated in block 2745. In some embodiments, thisdose of dextrose can be delivered in addition to a low dose of thetreatment substance (e.g. a drug, insulin, glucose, etc.) beingdelivered to the patient continuously at a steady rate. The calculationof the dose of dextrose may take into account various factors including,for example, one or more estimated glucose concentrations, presence ofadditional drugs in the patient's system, time taken for dextrose to beassimilated by the patient, and the delivery method (e.g., continuousinfusion or bolus injection). In block 2750, a fluid delivery system(e.g., a system such as the optional subsystem 2780 shown in FIGS. 5 and6) delivers the calculated dose of dextrose to the patient.

In block 2740, if the estimated glucose concentration is greater thanthe desired concentration (e.g., the patient is hyperglycemic), a doseof insulin to be delivered is calculated in block 2755. In someembodiments, this dose of insulin can be delivered in addition to a lowdose of the treatment substance (e.g. a drug, insulin, glucose, etc.)being delivered to the patient continuously at a steady rate. Thecalculation of the dose of insulin may depend on various factorsincluding, for example, one or more estimated glucose concentrations inthe patient, presence of other drugs, type of insulin used, time takenfor insulin to be assimilated by the patient, method of delivery (e.g.,continuous infusion or bolus injection), etc. In block 2750, a fluiddelivery system (e.g., the optional subsystem 2780 shown in FIGS. 5 and6) delivers the calculated dose of insulin to the patient.

In block 2765, the method 2700 returns to block 2705 to await the startof the next measurement cycle, which can be within about one minute toabout one hour (e.g., every fifteen minutes or less, every 30 minutes orless, every 45 minutes or less, etc.). In some embodiments, the nextmeasurement cycle begins at a different time than normally scheduled incases in which the estimated glucose concentration lies outside theacceptable range of concentrations under the glycemic protocol. Suchembodiments advantageously allow the system to monitor response of thepatient to the delivered dose of dextrose (or insulin). In some suchembodiments, the time between measurement cycles is reduced so thesystem can more accurately monitor analyte levels in the patient.

Examples of Some Possible Additional or Alternative Analytes

Although examples of control and/or monitoring has been described in theillustrative context of glycemic control, embodiments of the systems andmethods can be configured for control and/or monitoring of one or moreof many possible analytes, in addition to or instead of glucose. Monitorand/or control of analytes can be particularly helpful in ICUs, whichreceive trauma patients. For example, another parameter that can bemonitored is level of Hemoglobin (Hb). If the Hb level of a patient goesdown without an apparent external reason, the patient could be sufferingfrom internal bleeding. Indeed, many ICU patients (some estimate as manyas 10%) suffer from what appears to be spontaneous internal bleedingthat may not be otherwise detectable until the consequences are toodrastic to easily overcome. In some embodiments, level of Hb can bemeasured indirectly, because its relationship to oxygen in the veins andarteries (at different points in the vasculature with respect to theheart and lungs) is understood. In some embodiments, the apparatus,systems and methods described herein can be useful for measuring a levelof Hb.

Another parameter that can be monitored is lactate level, which can berelated to sepsis or toxic shock. Indeed, high levels and/or rapid risein lactate levels can be correlated to organ failure and oxygenationproblems in the blood and organs. However, other direct measures of thebiological effects related to lactate level problems can be difficult tomeasure, for example, only becoming measurable with a delay (e.g., 2-6hours later). Thus, measurement of lactate level can help provide avaluable early warning of other medical problems. Indeed, if a problemwith lactate levels is detected, a nurse or doctor may be able toprevent the correlated problems by providing more fluids.

Another parameter that can be monitored is central venous oxygensaturation (ScvO2). It can be advantageous to try to maintain an ScvO2of 65-70% or greater in ICU patients (to help avoid sepsis, forexample). In some embodiments, the apparatus, systems, and methodsdescribed herein can be useful for measuring a level of ScvO2.

Levels of lactate and ScvO2 in a patient can be used together to provideinformation and/or warnings to a health care provider, which can beespecially useful in an ICU setting. For example, if lactate and ScvO2are both high, a warning can be provided (e.g., automatically using analarm). If lactate is high, but ScvO2 is low, a patient may benefit fromadditional fluids. If ScvO2 is high, but lactate is low, a cardiacproblem may be indicated. Thus, a system that provides information aboutboth lactate and ScvO2 can be very beneficial to a patient, especially,for example, in the ICU environment. Although lactate and ScvO2 havebeen used as an illustrative example, in other embodiments differentcombinations of analytes can be monitored and used to provideinformation and/or warnings (e.g., to a patient and/or health careprovider).

Treatment Dosing System

Some implementations of a hospital's TGC protocol suffer fromdisadvantages. For example, in some healthcare environments (e.g., anICU) healthcare providers such as nurses may not have readily availablea paper insulin protocol that is sometimes used with IV insulin drips aspart of the TGC protocol. As a result, such healthcare providers mayhave to “estimate” the next required insulin dose adjustment or may haveto leave the patient's care in order to find the appropriate protocol.Further, when a new insulin dose is estimated, there is a risk thatthere may be a transcription error if the healthcare providerincorrectly inputs a new dose rate into an IV delivery pump. In suchexamples, an “estimated” rate is typically considered to be a deviationfrom the hospital's TGC protocol. Hospitals refine their insulinprotocols and generally seek “high compliance” with the insulin protocolin order, for example, to improve quality of care. Accordingly, in someembodiments, the patient monitoring system (e.g. 2630 of FIG. 26)advantageously is configured to determine insulin doses in compliancewith the TGC protocol.

In some embodiments, the insulin dose rate adjustments are determinedfrom one or more previously-made glucose readings and the currentglucose reading. One or both glucose readings can be determined by thepatient monitoring system (e.g., by the monitoring apparatus 2632 ofFIG. 26) and/or can be input to the patient monitoring system (e.g., viathe HIS interface software 2650). Possible advantages of determiningglucose readings with the system patient monitoring system includeincreased precision, reduced transcription errors, and near real-timeaccess to the most current patient readings.

In some embodiments, the patient monitoring system may comprise atreatment dosing system including a treatment dosing software (e.g.insulin dosing software 2652 of FIG. 26). In some embodiments, thedosing software is configured to include a treatment dosing protocol(e.g. an insulin protocol and/or TGC protocol). For example, the dosingsoftware may include the hospital's current, approved, local insulinprotocol. If an adjustment to a patient's insulin dose should be madebecause of the patient's current glucose values, the patient monitoringsystem can be configured to calculate the next recommended (orsuggested) treatment dose. The calculation of the next recommendedtreatment dose can be made at least in part based on the insulin dosingprotocol for the particular hospital. In some embodiments, informationrelated to the recommended treatment dose is output on the userinterface (e.g., the user interface 2400 and/or a display graphic asshown in FIGS. 28A-F). For example, the user interface may display thecurrent rate of dose and/or infusion, the dose type (e.g., bolus orsteady (basal) rate), and the recommended dose. A healthcare providermay use the information output by the user interface to adjust theactual dose value, as needed by a specific patient condition, and mayinitiate infusion. In some embodiments, the patient monitoring systemperforms the calculation of recommended dose, makes the adjustments tothe actual dose value, and provides this dose value to the patient, forexample, by infusion with the fluid system kit 2634 of FIG. 26. In someembodiments, a control system (e.g. fluid system controller 405 of FIG.4) in communication with the patient monitoring system can be configuredto provide instructions to an infusion pump fluidically connected to thesource of infusion fluid to start infusion. The control system may alsobe configured to adjust the pump rate of the infusion fluid to deliverthe recommended dose to the patient at a basal rate or as a bolusinjection.

FIG. 28A schematically illustrates an example of a display graphic 2800for use with an embodiment of the user interface 2400. The displaygraphic 2800 can be output by, for example, a touchscreen display deviceso that a user can view the information on the display graphic 2800 andactuate suitable insulin dosing controls. In other embodiments, buttons,keys, a mouse, or other input device can be used instead of (or inaddition to) touchscreen buttons. The embodiment of the display graphic2800 shown in FIG. 28A includes a suggested dose graphic 2804, an actualdose graphic 2808, dose decrement and increment buttons 2812 a and 2812b, and dosing control buttons 2816, and 2820. In other embodiments, thegraphics and buttons schematically illustrated in FIG. 28A can bearranged differently, and the display graphic 2800 may includeadditional and/or different information and controls.

In this embodiment, the suggested dose graphic 2804 includes a suggesteddose rate (e.g., 4 ml/hr) and a title graphic (“Insulin Dose”). Asdescribed above, the suggested dose rate can be calculated using thedosing software. The actual dose graphic 2708 includes a graphicrepresentation of the current, actual dose (e.g., 4 ml/hr). In thisembodiment, the suggested dose graphic 2808 and the actual dose graphic2808 use alphanumeric graphics to output dose information. In otherembodiments, the graphics 2804, 2808 may output dose information using,for example, trend graphs, bar or pie charts, symbols, and so forth.Advantageously, the values for the suggested and actual doses aredisplayed in a sufficiently large graphic font that a user can readilyread the values, which reduces potential error in dosing the patient. Inthe example shown in FIG. 28A, a steady (basal) infusion rate (e.g., 4ml/hr) is shown. In other embodiments, the display graphic 2800 may showa suggested bolus dose in addition to, or instead of, a steady state(basal) dose.

In this illustrative example, the actual dose and the recommended doseare the same (e.g., 4 ml/hr), but this is not a limitation. In a typicalimplementation, if the actual dose differs from the suggested dose, auser may adjust the actual dose value by actuating (e.g., pressing on atouchscreen) a decrement button 2812 a and/or an increment button 2812 buntil the actual dose equals the suggested dose. The decrement andincrement buttons 2812 a and 2812 b can be graduated in any suitabledose fractions (e.g., 0.1 ml/hr or some other amount).

The dosing control buttons include a cancel button 2816 and an infusebutton 2820. The cancel button 2816 can be used to stop, and the infusebutton 2820 can be used to actuate an infusion pump coupled to theinfusion fluid source and start, infusion of the insulin dose. In otherembodiments, additional or different infusion control buttons can beused.

In some embodiments, a control system (e.g. fluid system controller 405of FIG. 4) configured to provide instructions to an infusion pumpfluidically connected to a source of infusion fluid may comprise thedisplay graphic 2800. A health care provider or a user may actuate theinfusion pump or control the pump rate through the display graphic 2800and the control system. Moreover, the patient monitoring system canallow a user to control delivery of infusion fluids using controls on agraphic user interface of the monitoring system, even if the infusionfluids are pumped by a separate system that is not contained within thesame housing as the patient monitoring system. For example, themonitoring system can have built in wireless connectivity that canlocate infusion pumps (e.g., those that have wireless capabilities) inthe vicinity and establish communication with them. The monitoringsystem can allow a user to control those external infusion pumps throughits own control interface (e.g., through its display graphic describedherein). In some embodiments, the monitoring system can wirelesslysearch for an infusion pump delivering total parenteral nutrition (TPN),for example, and, with a handshake protocol, query that infusion pumpfor its hourly rate. This information can affect various outputs fromthe system (including, for example, a dose or rate suggested by theinsulin dosing algorithm). The monitoring system can do the same with aninfusion pump that is delivering insulin, and provide remote control ofthat pump through the monitoring system's graphic user interface, forexample.

The display graphic 2800 can be output on to any suitable monitor oroutput device (e.g., a touchscreen display). For example, in someembodiments, the display graphic 2800 is displayed on the user interface2400, e.g., adjacent an outer boundary of the example Ul graphic shownin FIGS. 24 and 25. In other embodiments, the display graphic 2800 isshown instead of the trend indicators 2816. In yet other embodiments,the display graphic 2800 is output with optional patient identificationinformation. Many variations are possible.

Accordingly, certain embodiments of the patient monitoring system (e.g.system 2630 of FIG. 26) can be used as an infusion pump, actuatableusing an embodiment of the display graphic 2800. In certain suchembodiments, a healthcare provider advantageously will be able tocontrol insulin delivery through the same patient IV access line.Embodiments of patient monitoring system that are configured to includea treatment dosing protocol (e.g. insulin protocol and/or a TGCprotocol), to determine a patient treatment dose based on patientglucose reading(s), and to deliver a recommended treatment dose to thepatient via a fluidic system (e.g. the fluid system kit 26134 of FIG. 26or via an infusion pump, for example, infusion pump 518 of FIG. 5) mayhave one or more of the following potential benefits: increasedcompliance with a treatment dosing protocol, reduction in treatmentdosing errors, time savings for healthcare providers, and greater IVaccess efficiency by delivery of some or all TGC-related medicamentsthrough a common IV line (e.g., a proximal port of a central venouscatheter or a lumen of a peripherally inserted central catheter).

FIGS. 28B-28F schematically illustrate embodiments of a display graphiccomprising a graphic user interface. These figures illustrate how ananalyte detection system can be configured to have a numerical displaymode (see, e.g., 2822) and a trend display mode (see, e.g., 2824) todisplay the present and/or historical concentration of one or moreanalytes (e.g. glucose, ScvO2, lactate, etc.). Similar to the embodimentillustrated in FIG. 28A, the embodiments illustrated in FIGS. 28B-28Fcan also provide information related to suggested and/or actual insulindose and enable the user or health care provider to control (e.g.,start, cancel, increase, decrease, etc.) delivery of insulin.

FIG. 28B shows an example of an embodiment of the display graphic 2800.In this example, the concentrations of three analytes; glucose, ScvO2and lactate are displayed on a screen of the display graphic 2800. Theconcentration can be displayed as a number (see, e.g., 2822) or as atrend line (see, e.g., 2824), or both. In some embodiments, theconcentration can be displayed as a trend graph of the concentrationversus time. The embodiments illustrated in FIG. 28B can also displaythe rate at which an infusion substance (e.g. insulin) is beingdelivered to the patient. For example reference numeral 2808 indicatesthat the amount of insulin being infused is 0.5 units/hr. In someembodiments, the display can be refreshed periodically to display themost current measured and/or stored values. The display can indicatewhen the last measurement was taken and/or the last time the display wasrefreshed (see, e.g., the text “rate confirmation at: 01:35”).

The example illustrated in FIG. 28B also illustrates a button 2812 thatcan be used to modify the rate at which insulin is being infused orotherwise control an analyte level. The display graphic, 2800 of FIG.28B can comprise additional buttons such as the Menu button 2828, whichcan provide additional functionalities.

A user or a health care provider can activate the button 2812 of FIG.28B to control infusion (e.g., modify the rate at which insulin oranother infusion substance is delivered). In some embodiments,activating the button 2812 can display a secondary screen as illustratedin FIG. 28C. The secondary screen may display the current rate at whichinsulin is being infused and the suggested rate at which insulin shouldbe infused. The secondary screen may comprise a dose increment button2812 a and a dose decrement button 2812 b to increase or decrease therate at which insulin is being infused. In some embodiments, a keypadmay be provided so that the user or health care provider can input thevalue for the insulin infusion rate. The secondary screen may comprisecontrols (e.g. cancel button 2816 or confirm button 2836) to cancel orconfirm the change in the insulin infusion rate. In the exampleembodiments illustrated in FIGS. 28C and 28D, a bolus dose button 2832can be provided to program a bolus dose that can be delivered to thepatient. If the user or the health care provider activates the bolusdose button 2832, the display graphic can display a bolus dose screenwhich displays a value for the bolus dose as illustrated in FIG. 28E. Insome embodiments, the bolus dose screen may display the remaining supplyof insulin as illustrated in FIG. 28E. The user or the health careprovider can change the amount of insulin bolus to be delivered andinstruct the system to deliver the bolus amount by activating the button2820. A confirmation screen 2840 may be displayed on the display graphic2800 as illustrated in FIG. 28F to confirm that the user or health careprovider wished to proceed with the bolus delivery. The embodimentsillustrated in FIGS. 28B-28F can comprise a touch screen to acceptinstructions and input from the user or the health care provider.

Although the insulin dosing software 2652 schematically illustrated inFIG. 26 and the display graphic 2800 schematically illustrated in FIGS.28A-28F are shown and described with respect to delivery of an insulindose, this is not a limitation, and in other embodiments, the dosingsoftware 2652 and the display graphic 2800 can be used to providesuitable doses and information related thereto for any suitable item oritems administered to a person, such as medicaments, drugs, foods orherbs, whether administered orally, intravenously, topically, etc. Thedosing software 2652 of FIG. 26 may calculate a recommended dose based(at least in part) on readings of suitable analyte(s) of interest in thepatient (e.g., glucose in the case of insulin dosing). The readings canbe performed by the system 2630 (e.g., with the monitoring apparatus2632) and/or by other analyte detection systems.

Examples Of Calculating Treatment Dose

In the method for providing glycemic control schematically illustratedin FIG. 27, the dextrose or insulin dose can be determined by atreatment dosing protocol. In some embodiments, the treatment dosingprotocol may determine the amount of dextrose or insulin to be deliveredby comparing the currently estimated value of glucose concentration witha target or desired value of glucose concentration. In some embodiments,the treatment dosing protocol may determine the treatment dose based onone or more of the following factors: the patient's medical conditionand medical history, the effectiveness of the treatment dose, thepresence or absence of other analytes, other drugs being administered,etc.

For example, in some embodiments, different types of insulin, listed inthe table below, having different activation properties can be used tocontrol the concentration of glucose in patients with hyperglycemia.

Quick-acting, such as the insulin analog lispro starts working: 5 to 15mins; active: 3 to 4 hrs. Short-acting, such as regular insulin startsworking: 30 mins; active: 5 to 8 hrs. Intermediate-acting, such as NPHinsulin, or lente insulin starts working: 1 to 3 hrs; active: 16 to 24hrs. Long-acting, such as ultralente insulin starts working: 4 to 6 hrs;active: 24 to 28 hrs. Insulin glargine and Insulin detemir startworking: 1 to 2 hrs; active, w/o peaks or dips: 24 hrs. A mixture of NPHand regular insulin starts working: 30 mins; active: 16 to 24 hrs.

In these embodiments, the insulin delivery rate can be calculated basedon factors such as the type of insulin, the time taken by the insulin tostart working, the time it remains active in the body, etc. In someembodiments the amount of treatment dose provided to control the analyteconcentration can be adjusted no more frequently than once every hour.In these embodiments, determining the treatment dose only on the basisof the comparison of the currently estimated value of glucoseconcentration with a desired value of glucose concentration and a fewother factors may be insufficient to accurately determine the treatmentdose required to provide TGC. Thus treatment dosing protocols thatdetermine the treatment dose by taking an average of two or moresequential glucose values or by calculating a rate of change of theglucose concentration over a period of time or both may be effective inproviding glycemic control.

FIG. 29 is a flowchart that schematically illustrates an embodiment of amethod 2900 of determining the treatment dose based on the averageconcentration of an analyte (e.g. glucose). In block 2905, an analytemonitoring system (e.g., the monitoring apparatus 2632 of FIG. 26)comprising a fluidic system (e.g. the fluid system kit 2634 of FIG. 26)obtains a sample of bodily fluid (e.g., a blood or blood plasma sample)from a source of bodily fluid (e.g., a patient) at an initial timeT_(initial). In some embodiments, the analyte monitoring system mayfurther comprise an analyte detection system that spectroscopicallyanalyzes the sample and obtains a measurement from the sample. Themeasurement may comprise an optical measurement such as, for example, aninfrared spectrum of the sample. In block 2910, the initialconcentration (C_(initial)) of an analyte (e.g. glucose) in the sampleis estimated from the measurement by using any of the methods describedabove. In block 2915, the initial concentration C_(initial) at timeT_(initial) is stored in an internal or an external database.

In some embodiments, the database can be located in a processing system(e.g. a computer system 2646 of FIG. 26) in electrical communicationwith the monitoring system. In some embodiments, the initialconcentration C_(initial) at time T_(initial) can be stored in a memorylocation of a memory device. The memory device can be located in themonitoring system or the processing system. In some embodiments, thememory device can be located external to the monitoring system and be inelectrical communication with the monitoring system. In someembodiments, an initial treatment dose D_(initial) can be determined anddelivered to the patient if the initial concentration C_(initial) of theanalyte is not within a predetermined range. The initial treatment doseD_(initial) may also be stored in the database or the memory location.

At a later time T_(i), a subsequent sample measurement is obtained asshown in block 2920. The time T_(i) may occur after a time interval ΔTfrom time T_(i-1) when a sample measurement was previously obtained. Forexample, a first sample measurement can be obtained at a first time T₁which occurs after a time interval ΔT from the initial time T_(initial)and a second sample measurement can be obtained at a second time T₂which occurs after a time interval ΔT from the first time T₁ and so on.The time interval ΔT may range anywhere from 5 minutes to 15 minutes. Insome embodiments, the time interval ΔT may be less than 5 minutes orgreater than 15 minutes. In block 2930, the concentration C_(i) of thesame analyte at time T_(i) is estimated from the obtained samplemeasurement. The method 2900 then proceeds to block 2940 wherein theestimated concentration C_(i) of the analyte is compared to apredetermined range. The predetermined range can be determined by takinginto account various factors such as a patient's medical condition, themedications and drugs being administered to the patient, etc. In someembodiments, the predetermined range is a glucose concentration in arange from about 70 mg/dL to about 110 mg/dL. If in block 2940, theconcentration C_(i) of the analyte is within the predetermined range,then the method 2900 moves to block 2950 where the value of theestimated concentration C_(i) of the analyte at time T_(i) is stored inthe database or the memory location. The method 2900 then returns toblock 2920 to obtain a next sample measurement after a time interval ΔT.

However, if in block 2940, the estimated concentration of the analyteC_(i) is determined to be not within the predetermined range, then themethod 2900 proceeds to block 2960 wherein an average concentrationC_(avg) of the analyte is calculated. In some embodiments, the averageconcentration C_(avg) can be calculated by taking an arithmetic mean ofthe estimated concentration C_(i) and one or more previous concentrationvalues stored in the database or the memory location and is given by theequation:

${C_{avg} = \frac{C_{i} + {\sum\limits_{k = 1}^{n}C_{i - k}}}{n + 1}},$where n is an integer greater than or equal to 1.

In the above equation, the variable C_(i) corresponds to the currentlyestimated concentration value and the variables C_(i-1), C_(i-2), . . ., C_(i-n) correspond to the concentration values previously obtained. Insome embodiments, the average concentration C_(avg) can be calculated bytaking a weighted average of the estimated concentration C_(i) and oneor more previous concentration values and is given by the equation:

${C_{avg} = \frac{{w_{i}C_{i}} + {\sum\limits_{k = 1}^{n}{w_{i - k}C_{i - k}}}}{w_{i} + {\sum\limits_{k = 1}^{n}w_{i - k}}}},$where n can be an integer greater than or equal to 1.

The weights w_(i) and w_(i-k) can be determined in a variety of ways.For example, in some embodiments the weight w_(i) associated with thecurrent estimated concentration value C_(i) may be greater than theweights w_(i-k) associated with the previous concentration values. Insome embodiments, a greater weight can be assigned to a concentrationvalue that is either abnormally high or abnormally low. In someembodiments, by contrast a smaller weight can be assigned to aconcentration value that is either abnormally high or abnormally low.

The method 2900 then proceeds to block 2970 where a treatment dose ofdextrose or insulin can be determined according to a glycemic controlprotocol based at least in part on the calculated average concentrationC_(avg). In some embodiments, the treatment dose of dextrose or insulincan be determined according to a glycemic control protocol based on thecalculated average concentration C_(avg) and variety of factors such aspatient's sensitivity to the treatment drug (e.g. insulin), thetreatment dosing history, the effectiveness of the treatment dose, thepresence or absence of other analytes, other drugs being administered,etc. In some embodiments, the determined treatment dose can be displayedto a health care provider on a display graphic (e.g. display graphic2800 of FIG. 28). In block 2980 the determined treatment dose can bedelivered to the patient by a fluid delivery system or a fluid infusionsystem (e.g., a system such as the subsystem 2780 shown in FIGS. 5 and6). In some embodiments, a control system (e.g. fluid system controller405 of FIG. 4) can be configured to provide instructions to an infusionpump fluidically connected to a source of infusion fluid to startinfusion. The control system may also be configured to adjust the pumprate of the infusion fluid to deliver the recommended treatment dose tothe patient at a basal rate or as a bolus injection. In someembodiments, the treatment dose can be delivered to the patient inaddition to a low dose of the treatment drug (e.g. insulin or glucose)being delivered to the patient continuously at a steady rate. In someembodiments, the healthcare provider may actuate the infusion pumpfluidically connected to a source of infusion fluid through a graphicuser interface (e.g. display graphic 2800 of FIG. 28). In someembodiments, the health care provider may provide instructions regardingthe pump rate to the infusion pump through a graphic user interface(e.g. display graphic 2800 of FIG. 28). In block 2990 the method 2900returns to block 2950 where the value of the estimated concentrationC_(i) of the analyte at time T_(i) is stored in the database or thememory location.

FIG. 30 is a flowchart that schematically illustrates an embodiment of amethod 3000 of determining the treatment dose based on the rate ofchange of the concentration of an analyte (e.g. glucose). The method3000 differs from the method 2900 in that if in block 2940, theestimated concentration of the analyte C_(i) is determined to be notwithin the predetermined range, then the method 3000 proceeds to block3060 where a rate of change of the concentration R_(c) of the analyte iscalculated. The rate of change of the concentration of the analyte R_(c)can be calculated in a variety of ways. In some embodiments, the rateR_(c) can be calculated from the current estimated concentration of theanalyte C_(i) at time T_(i) and the previously determined concentrationof the analyte C_(i-1) at time T_(i-1) stored in the database or memorylocation and is given by the following equation:

$R_{c} = \frac{C_{i} - C_{i - 1}}{T_{i} - T_{i - 1}}$

In some embodiments, the rate R_(c) can be calculated from the currentlyestimated concentration of the analyte C_(i) at time T_(i) and severalpreviously determined values for the concentration of the analyte storedin the database or memory location. In the method 3000, the treatmentdose is determined using a glycemic control protocol based at least inpart on the rate of change R_(c) of the concentration of the analyte asshown in block 3070. In some embodiments, determining the treatment dosebased on the rate of change R_(c) of the concentration of the analytecan ensure that the treatment dosing protocol responds to certainextreme conditions such as rapid change in the concentration of theanalyte (e.g. glucose). In some embodiments, such rapid change in theconcentration of the analyte can indicate that the patient's medicalcondition is unstable or critical. In some embodiments, the rapid changein the concentration can be an indicator of a failure of the measurementsystem or a part thereof.

FIG. 31A is a flowchart that schematically illustrates an embodiment ofa method 3100 of determining the treatment dose based on the currentestimated concentration or the average concentration of an analyte (e.g.glucose) and the rate of change of the concentration of the analyte. Themethod 3100 determines the treatment dose using a glycemic controlprotocol based at least in part on the average concentration C_(avg) ofthe analyte and the rate of change of the concentration R_(c) of theanalyte as shown in block 3170. The average concentration C_(avg) andthe rate of change of the concentration R_(c) can be calculated by oneor more of the methods described above. In some embodiments, asillustrated in FIG. 31B, the treatment dose can be determined using aglycemic control protocol based at least in part on the currentlyestimated concentration C_(i) and the rate of change of theconcentration R_(c) of the analyte.

Treatment Dose Feedback System

As described above, in some embodiments, the analyte monitoring systemcan be configured to control the concentration of one or more analyte byinfusing a treatment dose calculated by a treatment dosing protocol.However, the analyte monitoring system or the healthcare provider maynot have feedback regarding the effectiveness of the treatment dosesuggested by the treatment dosing protocol. Thus it may be advantageousto have a system that can both: (i) predict the concentration of ananalyte (e.g. glucose) at a future time based on the treatment dosesuggested by the treatment dosing protocol; and (ii) provide feedback tothe healthcare provider.

As described above, an analyte monitoring apparatus comprising a fluidicsystem (e.g. the fluid system kit 2634 of FIG. 26) can obtain a sampleof bodily fluid (e.g., a blood or blood plasma sample) from a source ofbodily fluid (e.g., a patient) and estimate the concentration of one ormore analytes in the sample several times during an hour. Theconcentration of the one or more analytes can be stored in a measurementhistory that can be accessed later. The measurement history may compriseone or more stored databases or memory locations.

In some embodiments, the measurement history can be located in aprocessing system (e.g. a computer system 2646 of FIG. 26) in electricalcommunication with the monitoring system. In some embodiments, theconcentration of the one or more analytes can be stored in a memorylocation of a memory device. The memory device can be located in themonitoring system or the processing system. In some embodiments, thememory device can be located external to the monitoring system and be inelectrical communication with the monitoring system. FIG. 32 illustratesan embodiment of a measurement history 3200 that stores the time ofmeasurement T_(i), the estimated or measured concentration of an analyte(e.g. glucose) C_(i) and the treatment dose D_(i) (of insulin or sugar,for example) administered to the patient. In some embodiments, themeasurement history 3200 may store information regarding estimated ormeasured concentration of other analytes. Other embodiments of themeasurement history are also possible.

If the estimated or measured concentration of an analyte (e.g. glucose)is not within an acceptable range, then a healthcare provider mayadminister a treatment dose based on a treatment dosing protocol tobring the concentration of the analyte within the acceptable range. FIG.33 schematically illustrates steps in a method to provide feedback tothe monitoring and/or dosing system (and, e.g., the healthcare provider)regarding the effectiveness of the treatment dose suggested by thetreatment dosing protocol. Feedback can be provided by a feedback system3405 illustrated in FIG. 34 which is in electronic communication withthe analyte monitoring apparatus 2632 and/or the computer system 2646 ofFIG. 34. Referring to FIG. 33, in block 3305 the feedback system 3405reads the treatment dose input by the healthcare provider or determinedby the treatment dosing software. The treatment dose can be put in tothe system in a variety of ways. For example, in one embodiment, thehealthcare provider may input the treatment dose using a keyboard. Insome embodiments, the healthcare provider may input the treatment doseusing a touch screen. In some embodiments, the treatment dose can beprovided automatically (e.g. by computer).

In block 3315 the feedback system 3405 accesses the measurement history(e.g. the measurement history 3200 illustrated in FIG. 32) that storesthe previously determined values for the concentration of the analyteand the values for a treatment dose previously administered. The method3300 then proceeds to block 3320 where the feedback system 3405calculates a predicted value for the concentration of the analyte at afuture time (e.g. in the next hour) based on the previously determinedvalues for the concentration of the analyte and the treatment dosinghistory. In some embodiments, the calculation may predict the value forthe concentration of the analyte at a future time by extrapolating theconcentration of the analyte assuming that the patient's sensitivity tothe treatment drug (e.g. insulin) remains the same and by furtherassuming that the amount of medications and drugs being administered tothe patient remain the same. For example, in some embodiments, thefeedback system 3405 may assume that treatment dose input by thehealthcare provider will not change over the next several timedurations.

In block 3330, the predicted value for the concentration of the analyteis compared with a predetermined range. The predetermined range can bedetermined by taking into account various factors such as a patient'smedical condition, the medications and drugs being administered to thepatient, etc. In some embodiments, the predetermined range may be aglucose concentration in a range from about 70 mg/dL to about 110 mg/dL.If in block 3330, the predicted concentration of the analyte isdetermined to be within the predetermined range, then the method 3300moves to block 3340 where the treatment dose input by the healthcareprovider is stored in the measurement history.

However, if in block 3330, the predicted concentration of the analyte isdetermined to be not within the predetermined range, then the method3300 proceeds to block 3360 where feedback is provided (e.g. to thehealthcare provider or analyte monitoring system) that the predictedconcentration of the analyte at a future time may be outside thepredetermined range if the treatment dose input to the system isdelivered to the patient. The system or the healthcare provider maychange the treatment dose based on the feedback. In some embodiments,the feedback system 3405 can be configured to automatically stop theflow of the infusion fluid (e.g. glucose or insulin) based on the trendor a value of the concentration of one or more analytes. For example, inthe case where the analyte of interest is glucose and the infusion fluidis insulin, the feedback system 3405 may stop the flow of insulin if theconcentration of glucose is low enough to be life threatening or if thetrend of successive glucose measurements indicated that theconcentration of glucose may drop to levels that may to harmful to thepatient.

In some embodiments, the feedback system 3405 can provide feedbackregarding one or more drugs being administered to the patient withoutrequiring an input from the healthcare provider. In some embodiments thefeedback system 3405 can spectroscopically analyze the infusion fluid asit flows out of the infusion pump and/or source of infusion fluid (e.g.518, 520 or 2782 of FIG. 5) through the infusion fluid tubes (e.g. 514,516 or 2784 of FIG. 5) to determine the contents of the infusion fluid.For example, in some embodiments the feedback system 3405 may irradiatethe infusion fluid with three or more wavelengths. In some embodiments,the wavelengths can be selected from the wavelength range ofapproximately 275 nm to 310 nm. In some embodiments, the wavelengths canbe selected from the near infrared or infrared range of wavelengths. Thefeedback system 3405 can then obtain one or more spectra from theradiation reflected, transmitted and/or scattered by the infusion fluidto determine the contents of the infusion fluid. The spectra obtained bythe feedback system 3405 can be compared with a catalog of drug orchemical spectra to identify the contents of the infusion fluid. In someembodiments, the spectra can be further analyzed to determine theconcentration of the various contents of the infusion fluid.

The feedback system 3405 can comprise a watch list including the drugsor chemicals that may be detrimental to the health of the patient. Theidentified contents of the infusion fluid can be compared with the watchlist. If a particular drug or chemical present in the watch list isdetected in the infusion fluid, then the feedback system 3405 can beconfigured to shut off the infusion system delivering that particulardrug or chemical to the patient. In addition, the feedback system 3405may provide alerts or warnings to the healthcare provider and requestconfirmation from the healthcare provider before resuming the flow ofthat particular drug or chemical. In some embodiments, the feedbacksystem 3405 can be configured to prevent the flow of a drug or chemicalif the concentration of that drug or chemical in the infusion fluid isdetermined to be outside an acceptable range. For example, the systemcan issue an alert or warning to the healthcare provider.

Dilution Calibration

As described above, in certain embodiments, the systems and methodsdetermine a concentration of an analyte such as, for example, glucose,in a bodily fluid sample such as, for example, whole blood or bloodplasma. In some cases, the concentration of a blood plasma analyte canbe affected by dilution of the whole blood sample from which the plasmais obtained. Dilution of a sample may occur during processing of thesample (e.g., by addition of a diluent to the sample), during operationof the sampling apparatus (e.g., by mixing of the sample with diluentsin the apparatus), and so forth. For example, dilution may occur if ananticoagulant (e.g., heparin) is added to a blood sample to preventclotting. Also, dilution may occur as a fluid sample travels through theapparatus, for example, through accumulation of residual diluent fluids(e.g., saline solution) in tubing.

Generally, dilution of a bodily fluid sample will result in the analyteconcentration measured from the diluted sample being less than theanalyte concentration present in the patient's body. Because diluentsare more likely to reside in the plasma portion of the blood, dilutioneffects may be greater for analyte concentrations measured in bloodplasma. Accordingly, it may be advantageous to calibrate a measuredanalyte concentration for some or all of the effects of dilution. Insome embodiments, a measured analyte concentration is corrected fordilution to provide an estimate of analyte concentration that is morerepresentative of the concentration in the patient's body.

As described above, certain embodiments of the disclosed systems andmethods are directed to the measurement of blood plasma analytes insamples of whole blood. Since fluid diluents typically reside in bloodplasma rather than in non-plasma components, it may be advantageous todetermine the relative amounts of plasma and non-plasma components in awhole blood sample.

Whole blood includes fluid components (e.g., blood plasma) and non-fluidcomponents (e.g., red blood cells, white blood cells, platelets, etc.).In a typical sample of whole human blood, red blood cells constituteapproximately 45% of the blood volume, and white blood cells constituteapproximately 1% of the blood of the blood volume. Platelets are small,non-fluid blood components that typically remain in the plasma, evenafter the plasma is separated (e.g., via centrifuging). Consequently,blood plasma typically constitutes approximately 54% of the bloodvolume.

The relative amounts of plasma and corpuscles in a whole blood samplecan be determined in many ways, for example, by using a hematocrit,which is an instrument that separates a blood sample by centrifugation.The hematocrit value (commonly referred to as “Ht” or “HCT”) is thepercentage of red blood cells in whole blood. The hematocrit value canbe determined by centrifuging a sample of whole blood in a graduatedtube, a process which packs the red blood cells into the bottom of thetube. Values of the volume of packed red blood cells and the totalvolume of the blood sample are measured, and the percentage of red bloodcells in the total sample, Ht, is calculated as the ratio of thesevalues. As noted above, red blood cells form the bulk of the non-plasmacomponent of blood. Accordingly, the fraction of blood plasma in wholeblood is approximately 1-Ht.

The hematocrit value can be estimated without separating red blood cellsfrom whole blood in a centrifuge. One method for estimating Ht uses thefact that hemoglobin predominantly resides in the red blood cells. Theconcentration of hemoglobin in whole blood can be determined, forexample, by optical spectroscopy of the blood sample. Apparatus andmethods for optical measurements of blood are described, for example, inU.S. Pat. No. 5,385,539, issued Jan. 31, 1995, entitled “APPARATUS FORMONITORING HEMATOCRIT LEVELS OF BLOOD,” the entire disclosure of whichis hereby incorporated by reference herein. The hematocrit, Ht, has beenfound to be related to the concentration of hemoglobin in whole blood,Hb, as follows:Ht (%)=3Hb/(g/dL)  (1)Accordingly, a measurement of hemoglobin concentration, Hb, can beconverted into a measurement of hematocrit, Ht, (and vice versa) byapplication of Equation (1). Therefore, embodiments of analyte detectionsystems can be configured with hematocrit sensors, hemoglobin sensors,or a combination thereof to determine, as appropriate, hematocrit and/orhemoglobin concentration.

Hematocrit (and/or hemoglobin concentration) can be measured via othertechniques as well. For example, one example method for estimating Htuses changes in the electrical conductivity through whole blood, whereblood cells act as electrical insulators. Electrical conductivityapparatus and methods are described, for example, in U.S. Pat. No.6,058,934, issued May 9, 2000, entitled “PLANAR HEMATOCRIT SENSORINCORPORATING A SEVEN-ELECTRODE CONDUCTIVITY MEASUREMENT CELL,” theentire disclosure of which is hereby incorporated by reference herein.Another example method for estimating Ht uses acoustic ultrasoundmeasurements to determine Ht, for example, as described in U.S. Pat. No.4,854,170, issued Aug. 8, 1989, entitled “APPARATUS AND METHOD FOR USINGULTRASOUND TO DETERMINE HEMATOCRIT,” the entire disclosure of which ishereby incorporated by reference herein. In other techniques, hematocritand/or hemoglobin concentration can be measured using a combination ofapproaches such as, for example, optical and acoustic techniques asdescribed in U.S. Pat. No. 6,751,490, issued Jun. 15, 2004, entitled“CONTINUOUS OPTOACOUSTIC MONITORING OF HEMOGLOBIN CONCENTRATION ANDHEMATOCRIT,” the entire disclosure of which is hereby incorporated byreference herein. Embodiments of the systems and methods disclosedherein may use one or more of the above-described example approaches (orother approaches) to measure hematocrit and/or hemoglobin concentrationin a fluid sample.

In certain embodiments, an analyte concentration, g, is calibrated forthe effects of dilution by determining or inferring a volume of diluentfluid added to the bodily fluid sample during processing of the sample,operation of the analyte detection system, and so forth. The estimatedanalyte concentration can be calibrated to account for the added diluentvolume. For example, in some embodiments, one or more measurements ofhematocrit (and/or hemoglobin concentration) in the fluid sample aremade before and after dilution, and these measurements are used to atleast partially correct an estimated analyte concentration for theeffects of dilution. Examples of dilution calibration methods andsystems will now be described.

Example Dilution Calibration Systems

Any of the example analyte detection systems (and/or fluid handlingsystems) described herein can be used to provide dilution calibration.For example, FIGS. 35 and 36 schematically illustrate embodimentssuitable for using hematocrit and/or hemoglobin concentrationmeasurements to at least partially correct for dilution. Many of thecomponents shown in FIGS. 35 and 36 have been described above withreference to FIGS. 5 and 6. In the embodiments depicted in FIGS. 35 and36, the bubble sensor BS14 shown in FIG. 5 (reference numeral 552) andFIG. 6 has been interchanged with a hemoglobin sensor Hb14 (referencenumeral 3504 in FIG. 35). In some embodiments, the hemoglobin sensorHb14 is generally similar to the hemoglobin sensor 526 (Hb12) describedabove with reference to FIGS. 5 and 6. As will be described below, inthese embodiments, the hemoglobin sensor Hb12 is used to measurehemoglobin concentration of the fluid sample after drawing from the body(and before substantial dilution has occurred). The hemoglobin sensorHb14 is used to measure hemoglobin concentration after the fluid samplehas traveled through the tubing to the vicinity of the centrifuge (andtherefore after dilution may have occurred). These “before dilution” and“after dilution” measurements of hemoglobin concentration can be used toat least partially correct for the effects, if present, of dilution.

Although the embodiments shown in FIGS. 35 and 36 utilize a hemoglobinconcentration sensor Hb14, in other embodiments either (or both) of thehemoglobin concentration sensors Hb12 and Hb14 may be hematocritsensors. Further, although the bubble sensor BS14 (shown in FIGS. 5 and6) has been interchanged with the hematocrit sensor Hb14 in theembodiments shown in FIGS. 35 and 36, in other embodiments, thehematocrit sensor Hb14 is provided in addition to the bubble sensor BS14. Also, in other embodiments the sensors Hb12 and Hb14 can be disposedat locations in the fluid handling network that are different than shownin FIGS. 5, 6, 35, and 36. For example, the sensor Hb12 can be locatedcloser to the patient tube 512 (T1), and the sensor Hb14 can be locatedcloser to (but downstream of) the anticoagulant valve 541. It isadvantageous for the sensors Hb12 and Hb14 to be disposed at locationsin the fluid handling network such that substantially all the dilutionof the fluid sample can be accounted for. Although two sensors Hb12 andHb14 are shown in FIGS. 35 and 36, in other embodiments three, four,five, six, or more sensors can be used to measure dilution of the fluidsample. For example, in some embodiments, sensors are positionedupstream and downstream of the location where an anticoagulant (e.g.,heparin) is added to the fluid sample. Such embodiments advantageouslycan be used to calibrate for dilution by the anticoagulant.

An example of collection of a fluid sample will now be described withreference to FIG. 35. With the valves 542 (PV1), 559 (V7 b), and 561 (V4b) closed, a first pump 522 (pump #1) is actuated to draw sample fluidto be analyzed (e.g. blood) from a fluid source (e.g., a laboratorysample container, a living patient, etc.) up into the patient tube 512(T1), through the tube past the two flanking portions of the openpinch-valve 523 (V0), through the first connector 524 (C1), into thelooped tube 530, past the hemoglobin sensor 526 (Hb12), and into the Hbsensor tube 528 (T4). During this process, the valve 529 (V7 a) and 523(V0) are open to fluid flow, and the valves 531 (V1 a), 533 (V3 a), 542(PV1), 559 (V7 b), and 561 (V4 b) can be closed and therefore block (orsubstantially block) fluid flow by pinching the tube.

Before drawing the sample, the tubes 512 (T1) and 528 (T4) are filledwith saline and the hemoglobin (Hb) level is zero. The tubes that arefilled with saline are in fluid communication with the sample source(e.g., the fluid source 402). The sample source can be the vessels of aliving human or a pool of liquid in a laboratory sample container, forexample. When the saline is drawn toward the first pump 522, fluid to beanalyzed is also drawn into the system because of the suction forces inthe closed fluid system. Thus, the first pump 522 draws a relativelycontinuous column of fluid that first comprises generally nondilutedsaline, then a mixture of saline and sample fluid (e.g., blood), andthen eventually a nondiluted sample fluid.

The hemoglobin sensor 526 (Hb12) detects the concentration of hemoglobinin the sample fluid. As blood starts to arrive at the hemoglobin sensor526 (Hb12), the hemoglobin level rises. A hemoglobin level can beselected, and the system can be pre-set to determine when that level isreached. A controller such as the fluid system controller 405 of FIG. 4can be used to set and react to the pre-set value, for example. In someembodiments, when the sensed hemoglobin level reaches the pre-set value,a substantially undiluted sample is present at the first connector 524(C1). The preset value can depend, in part, on the length and diameterof any tubes and/or passages traversed by the sample. A nondilutedsample can be, for example, a blood sample that is not diluted withsaline solution, but instead has the characteristics of the rest of theblood flowing through a patient's body. The hemoglobin sensor 526 (Hb12)can measure the hemoglobin concentration of this “before dilution” bloodsample. A loop of tubing 530 (e.g., a 1-mL loop) can be advantageouslypositioned as illustrated to help insure that undiluted fluid (e.g.,undiluted blood) is present at the first connector 524 (C1) when thehemoglobin sensor 526 (Hb12) registers that the preset Hb threshold iscrossed. The loop of tubing 530 provides additional length to the Hbsensor tube 528 (T4) to make it less likely that the portion of thefluid column in the tubing at the first connector 524 (C1) has advancedall the way past the mixture of saline and sample fluid, and thenondiluted blood portion of that fluid has reached the first connector524 (C1). Accordingly, a possible advantage of embodiments using theloop of tubing 530 is that the “before dilution” hemoglobinconcentration measured by the sensor 526 (Hb12) is representative of the(non-diluted) hemoglobin concentration of the patient's body.

When sufficiently nondiluted blood is present at the first connector 524(C1), the fluid sample can be directed through the tube 534 (T3), pastthe connectors C6 and C2, and to the sample cell 548 for analysis. Whiletraveling through this tubing, the fluid sample can be diluted byaccumulation of saline solution, cleaning solution, etc. that has beenleft behind on the tube walls after cleaning or purging. Additionally,in some embodiments, an amount of anticoagulant (e.g., heparin) can beintroduced into the tube 534 (T3), and then the fluid sample is mixedwith the anticoagulant. As described above, the anticoagulant can beshuttled from the tube 540 into the anticoagulant valve tube 534 (T3) toprovide a controlled amount of anticoagulant into the tube 534 (T3),which thereby additionally dilutes the fluid sample. After addition ofthe anticoagulant (if desired), the fluid sample is pushed up theanticoagulant valve tube 534 (T3), through the connector C6, and throughthe second connector 546 (C2). Along this path, the fluid sample mayexperience further dilution from accumulation of fluids on the tubewalls. After passing the connector C2, the sample comes into sensingcontact with the hemoglobin sensor 3404 (Hb14), which determines an“after-dilution” hemoglobin concentration of the sample. The sample isthen pushed into the sample cell 548, which can be located on thecentrifuge rotor 550. The fluid in the sample cell is centrifuged, whichseparates blood corpuscles from the blood plasma and any diluentspresent in the plasma (e.g., heparin, saline, cleaning fluid, etc.).Concentration of analytes in the diluted blood plasma can be measured asdescribed above.

An example of the collection of a fluid sample in the fluid handlingembodiment schematically illustrated in FIG. 36 will be described.Collection of the fluid sample may be generally similar to thecollection described above with reference to FIG. 35. For example, bloodis drawn from a patient (or from a suitable extracorporeal conduit),through the tubes T1, T22, and T4 and into the loop. When the hemoglobinsensor Hb12 determines, via a “before dilution” hemoglobin measurement,that the loop contains undiluted blood, the blood sample is directed toconnector C1 and into line T2. If desired, as the blood sample passesthe connector C6 an anticoagulant (e.g., heparin) can be injected, whichdilutes the blood sample. The blood sample is then directed through thetubes T3 and T17 and passes the connector C2, where the hemoglobinsensor Hb14 performs an “after dilution” hemoglobin measurement. Theblood sample is then directed into the sample cell of the centrifuge,where the blood corpuscles are separated from a diluted volume of bloodplasma. A measurement of analyte concentration may then be performed onthe diluted plasma sample. As discussed above, as the blood sampletravels from the sensor Hb12 to the sensor Hb14, the blood sample can bediluted due to 1) accumulation of fluids (e.g., saline, cleaningsolution, etc.) left behind on the tube walls from a previous tubepurging/cleaning, and/or 2) injection, if desired, of an amount of aanticoagulant at the connector C6.

Example Dilution Calibration Methods

FIG. 37 is a flowchart illustrating an example method 3700 forcalibrating an analyte measurement in a fluid sample for dilution of thefluid sample. In block 3704, a fluid sample is obtained for measurement.The fluid sample may comprise whole blood, blood plasma, interstitialbody fluid, and so forth. The fluid sample can be obtained from asuitable fluid source (e.g., a laboratory sample container, a livingpatient, etc.). In many of the illustrative examples described herein,the fluid sample is a whole blood sample drawn from a patient, but thisis not intended to be a limitation to embodiments of the calibrationmethods.

In block 3708, a first property of the fluid sample is measured.Advantageously, the first property may be sensitive to dilution of thesample. For example, in some embodiments the first property ishematocrit and/or hemoglobin concentration, and the first property ismeasured by a blood sensor such as, e.g., a hematocrit sensor and/or ahemoglobin sensor. In other embodiments, the first property may be aconcentration of a particular component, analyte, or species in thefluid sample. Properties such as, for example, density and/or volume ofthe fluid sample can be measured. The first property may be ameasurement of a single parameter or characteristic of the fluid sampleor may include a group of measurements.

In block 3712, the obtained fluid sample is transported to a measurementsite capable of providing a measurement of an analyte in the fluidsample. For example, the obtained fluid sample can be transported by afluid handling network in an analyte detection system, such as, e.g.,the fluid handling networks schematically depicted in FIGS. 35 and 36.While being transported, the fluid sample may experience dilution causedby, for example, processing of the fluid sample (e.g., addition of oneor more diluents) and/or through routine operation of the fluidtransport network (e.g., accumulation in the sample of diluents presentin tubing in the fluid handling network). The amount of dilution can beknown and/or unknown. For example, the amount (e.g., volume) of ananticoagulant added to the sample can be known (or determinable), whilethe amount of diluent accumulated from the fluid handling network can beunknown (and dependent on how the system has been operated prior totransport of the sample).

In block 3716, a second property of the fluid sample is measured.Advantageously, the second property may be sensitive to dilution of thesample such that the amount of dilution can be determined fromcomparison of the first property and the second property. As discussedabove for the first property, the second property may includehematocrit, hemoglobin concentration, concentration of a particularcomponent, analyte, or species in the fluid sample, density, and/orvolume of the fluid sample. The second property may be a measurement ofa single parameter or characteristic of the fluid sample or may includea group of measurements. The second property may be the same as thefirst property (e.g., both the first and the second property may behematocrit), or the second property may be different from the firstproperty (e.g., the first property may be hematocrit and the secondproperty may be hemoglobin concentration).

In block 3720, a measuring apparatus performs a measurement of ananalyte concentration in a portion of the fluid sample. For example, themeasuring apparatus may comprise a spectroscopic analyte detectionsystem configured to measure the concentration of an analyte (e.g.,glucose) in plasma separated from a blood sample. The measuringapparatus may perform the analyte measurement on the fluid sample (e.g.,a whole blood sample) and/or a component of the fluid sample (e.g.,blood plasma separated from whole blood). Because of the possibleeffects of dilution of the fluid sample during transport in block 3712,the measured analyte concentration may not represent the analyteconcentration in the nondiluted fluid sample obtained in block 3704.Accordingly, in blocks 3724 and 3728, the measured analyte concentrationis calibrated for dilution of the fluid during transport. In someembodiments, the calibration at least partially corrects the measuredanalyte concentration for the dilution. For example, in block 3724 acalibration is determined based at least in part on the first propertyand the second property. Illustrative, non-limiting examples of thecalculation of the calibration will be presented below. In block 3728,the calibration is applied to the analyte concentration measured inblock 3720 to provide an at least partially dilution-calibrated estimatefor analyte concentration.

In some embodiments, one or more general purpose and/or special purposecomputers can be used to implement embodiments of the method 3700.Embodiments of the method 3700 can be represented as computer-executableinstructions on a computer-readable medium. For example, the fluidsystem controller 405 may control the measurements of the first andsecond properties in blocks 3708 and 3716 (e.g., using measurement ofhematocrit and/or hemoglobin concentration), and the algorithm processor416 may control the measurement and calibration of the analyteconcentration in blocks 3720-3728. In other embodiments, portions of themethod 3700 can be executed by processors that are remote from analytedetection system. In certain embodiments, some (or all) of the blocks3604-3728 can be combined or can be performed differently (or indifferent orders) than shown in the example method 3700 shown in FIG.37. Many variations are possible.

An example procedure for calibrating an analyte measurement for theeffects of dilution will now be described. This example is intended tobe illustrative and not to limit the scope of the dilution calibrationmethods. In this example, a measurement of hematocrit and/or hemoglobinin a blood sample is performed “before dilution” (e.g., in block 3708)and another hematocrit and/or hemoglobin measurement is performed “afterdilution” (e.g., in block 3716). For example, in the fluid systemembodiments shown in FIGS. 35 and 36, the “before dilution” measurementcan be provided by the hemoglobin sensor Hb12 and the “after dilution”measurement can be provided by the hemoglobin sensor Hb14. As describedabove, in other embodiments, additional hematocrit and/or hemoglobinmeasurements can be obtained. In such embodiments, the additionalmeasurements can be used to improve accuracy and/or precision of thedilution calibration according to any suitable statistical techniques(e.g., regression, least squares, maximum likelihood, outlier analysis,etc.).

In this example procedure, “before dilution” measurements are indicatedwith a subscript “0,” and “after dilution” measurements are indicatedwith a subscript “1.” Further, in this example, the blood sample will beconsidered to include corpuscles, e.g., red and white blood cells,(subscript “c”) and plasma (subscript “p”). In a volume of blood denotedby V, a volume V_(c) contains corpuscles, and the remaining volumeV_(p)=V−V_(c) contains plasma. Thus, hematocrit, Ht, can be written as

$\begin{matrix}{{Ht} = {\frac{V_{c}}{V} = {1 - \frac{V_{p}}{V}}}} & (2)\end{matrix}$If hemoglobin concentration, Hb, is used to estimate Ht, Equation (1)can be used to convert Hb to Ht (or vice versa).

The total amount of glucose in the plasma is denoted by G, and equalsthe plasma glucose concentration, g, multiplied by the plasma volumeG=gV_(p)  (3)

In this example, assume that as the blood sample is transported, it isdiluted with a volume AV of fluid having no glucose and no solids. Forexample, ΔV may represent the controlled amount of anticoagulant mixedwith the blood sample at the tube 534 (T3, shown in FIG. 35). Because noglucose and no solids are assumed to be added to the blood sample, thevalues of G and V_(c) do not change during dilution. Consequently,G₀=G₁=G  (4)V_(c0)=V_(c1)=V_(c)  (5)

The total blood volume and the plasma volume after dilution are relatedto the volumes before dilution and the dilution volume ΔV byV ₁ =V ₀ +ΔV  (6)V _(p1) =V _(p0) +ΔV.  (7)

The plasma glucose concentration after dilution, g₁, is determined bythe analyte detection system (e.g., in block 3720 of FIG. 37) and isthus a measured (known) quantity. Because the total amount of glucose,G, in the blood sample is assumed to be constant (no glucose is added bythe diluent fluid), the value of the plasma glucose concentration beforedilution, g₀, is unknown but may be related to g₁ from Equations (3) and(4): G=g₀V_(p0)g₁V_(p1). Combining this relationship with Equation (7)yields

$\begin{matrix}{{{\frac{g_{0}}{g_{1}} - 1} = \frac{\Delta\; V}{V_{p\; 0}}},} & (8)\end{matrix}$hence, the calibration of the plasma glucose measurement is related tothe amount of dilution, ΔV, of the blood sample. The “before dilution”plasma volume V_(p0) can be replaced with the “before dilution”hematocrit, Ht₀, by using Equation (2), which yields

$\begin{matrix}{{{\frac{g_{0}}{g_{1}} - 1} = \frac{\Delta\; V\text{/}V_{0}}{1 - {Ht}_{0}}},} & (9)\end{matrix}$where V₀ is the total blood volume before dilution.

In embodiments in which hemoglobin concentration, Hb, is measuredinstead of hematocrit, Ht, Equation (1) can be used in Equation (9) toyield

$\begin{matrix}{{{\frac{g_{0}}{g_{1}} - 1} = \frac{\Delta\; V\text{/}V_{0}}{1 - {3{Hb}_{0}}}},} & (10)\end{matrix}$where Hb₀ is measured in g/dL.

In some embodiments, the volumes ΔV and V₀ (or the ratio ΔV/V₀) and thevalue Hb₀ are measured, and Equation (10) is used to adjust the measuredplasma glucose concentration, g₁, to yield an estimate of the undilutedplasma glucose concentration, g₀. For example, in implementations whereaddition of an anticoagulant predominates dilution of the sample, theamount ΔV of the added anticoagulant can be measured (or otherwise know)and used in Equation (10) to calibrate the analyte concentrationmeasurement.

In other embodiments, the diluted hematocrit, Ht₁ (and/or the dilutedhemoglobin concentration Hb₁) is measured, and the volumes in Equation(10) are replaced with measured blood sample values. For example,because no solids are assumed to be added by the fluid diluent, thevolume of corpuscles in the sample, V_(c), is constant, and Equations(2) and (5) can be combined as V_(c)=V₀Ht₀=V₁Ht₁. Equation (6) can beused eliminate V₁ to yield

$\begin{matrix}{\frac{\Delta\; V}{V_{0}} = {\frac{{Ht}_{0}}{{Ht}_{1}} - 1.}} & (11)\end{matrix}$Consequently, measurements of hematocrit (and/or hemoglobinconcentration) “before dilution” and “after dilution” can be used toprovide an estimate of fractional sample dilution, ΔV/V₀.

Substituting Equation (11) into Equation (9) provides anotherrelationship that can be used to calibrate an “after dilution” glucosemeasurement to yield an estimate for the “before dilution” glucosemeasurement:

$\begin{matrix}{{{\frac{g_{0}}{g_{1}} - 1} = \frac{{{Ht}_{0}/{Ht}_{1}} - 1}{1 - {Ht}_{0}}},} & (12)\end{matrix}$or if hemoglobin concentration Hb is measured (see, Eq. (1)),

$\begin{matrix}{{\frac{g_{0}}{g_{1}} - 1} = {\frac{{{Hb}_{0}\text{/}{Hb}_{1}} - 1}{1 - {3{Hb}_{0}}}.}} & (13)\end{matrix}$Equations (12) and (13) can be rewritten to show how the estimate forthe “before dilution” analyte concentration g₀ is related to themeasured “after dilution” analyte concentration g₁:

$\begin{matrix}{{g_{0} = {g_{1}\left\lbrack {\frac{{Ht}_{0}}{{Ht}_{1}}\frac{\left( {1 - {Ht}_{1}} \right)}{\left( {1 - {Ht}_{0}} \right)}} \right\rbrack}},} & (14)\end{matrix}\begin{matrix}{g_{0} = {{g_{1}\left\lbrack {\frac{{Hb}_{0}}{{Hb}_{1}}\frac{\left( {1 - {3{Hb}_{1}}} \right)}{\left( {1 - {3{Hb}_{0}}} \right)}} \right\rbrack}.}} & (15)\end{matrix}$If there is no measurable dilution of the sample, the “before dilution”and the “after dilution” Ht and/or Hb measurements will be substantiallythe same (e.g., the factors in square brackets will be approximatelyequal to one), and Equations (14) and (15) demonstrate that, asexpected, g₀≈g₁. In some embodiments, the calibration shown in Equation(14) or (15) is not applied if the change between Ht₁ and Ht₀ (or Hb₁and Hb₀) is more representative of measurement errors by hematocrit(and/or hemoglobin) sensors than dilution of the sample. If measurabledilution of the sample occurs, the “before dilution” and “afterdilution” values for Ht (and/or Hb) will be different, and the factorsin square brackets in Equations (14) and (15) provide an approximatecorrection factor that at least partially accounts for the dilution.

Thus, for example, in an embodiment in which Hb₀, Hb₁, and g₁ aremeasured (e.g., the embodiments shown in FIGS. 35 and 36), Equation (13)(or Eq. (15)) provides a relationship that can be used to estimate the“before dilution” analyte concentration g₀. Although the above examplehas been described in terms of glucose concentration, this is not alimitation, and the example procedure described herein can be used tocalibrate concentration of any analyte measured in blood plasma.Further, Equations (2)-(15) can be readily modified if variousassumptions that went into their derivation are relaxed. For example, anappropriate calibration for an analyte concentration can be derived ifthe diluent fluid added to the blood sample contains a known amount (orconcentration) of the analyte of interest and/or blood solids. Also,Equations (12)-(15) can be modified if more than two hematocrit (and/orhemoglobin concentration) measurements are made while the blood sampleis being transported between the patient (or an extracorporeal fluidcontainer) and the analyte measurement apparatus (e.g., the centrifugeand spectroscopic analyzer). Many variations are contemplated, and anappropriate calibration may readily be determined for each suchvariation using the teachings herein. For example, in manyimplementations, the calibration will be a linear (e.g., affine)relationship, thus the “before dilution” concentration estimate will berelated to the “after dilution” concentration measurement according tog₀=Cg₁+D, where C is a calibration factor and D is a calibration offset.In the example calibration procedure described above, the calibrationoffset D=0, and the calibration factor C is the quantity in the squarebrackets in Equation (14) (if hematocrit is measured) or Equation (15)(if hemoglobin concentration is measured). In other embodiments, thecalibration offset is non-zero. For example, the calibration offset mayat least partially correct for a diluent fluid that also includes theanalyte of interest.

Reference throughout this specification to “some embodiments” or “anembodiment” means that a particular feature, structure or characteristicdescribed in connection with the embodiment is included in at least someembodiments. Thus, appearances of the phrases “in some embodiments” or“in an embodiment” in various places throughout this specification arenot necessarily all referring to the same embodiment and may refer toone or more of the same or different embodiments. Furthermore, theparticular features, structures or characteristics can be combined inany suitable manner, as would be apparent to one of ordinary skill inthe art from this disclosure, in one or more embodiments.

As used in this application, the terms “comprising,” “including,”“having,” and the like are synonymous and are used inclusively, in anopen-ended fashion, and do not exclude additional elements, features,acts, operations, and so forth. Also, the term “or” is used in itsinclusive sense (and not in its exclusive sense) so that when used, forexample, to connect a list of elements, the term “or” means one, some,or all of the elements in the list.

Similarly, it should be appreciated that in the above description ofembodiments, various features are sometimes grouped together in a singleembodiment, figure, or description thereof for the purpose ofstreamlining the disclosure and aiding in the understanding of one ormore of the various inventive aspects. This method of disclosure,however, is not to be interpreted as reflecting an intention that anyclaim require more features than are expressly recited in that claim.Rather, inventive aspects lie in a combination of fewer than allfeatures of any single foregoing disclosed embodiment.

Embodiments of the disclosed systems and methods can be used and/orimplemented with local and/or remote devices, components, and/ormodules. The term “remote” may include devices, components, and/ormodules not stored locally, for example, not accessible via a local bus.Thus, a remote device may include a device which is physically locatedin the same room and connected via a device such as a switch or a localarea network. In other situations, a remote device may also be locatedin a separate geographic area, such as, for example, in a differentlocation, building, city, country, and so forth.

Methods and processes described herein may be embodied in, and partiallyor fully automated via, software code modules executed by one or moregeneral and/or special purpose computers. The word “module” refers tologic embodied in hardware and/or firmware, or to a collection ofsoftware instructions, possibly having entry and exit points, written ina programming language, such as, for example, C or C++. A softwaremodule may be compiled and linked into an executable program, installedin a dynamically linked library, or may be written in an interpretedprogramming language such as, for example, BASIC, Perl, or Python. Itwill be appreciated that software modules may be callable from othermodules or from themselves, and/or may be invoked in response todetected events or interrupts. Software instructions may be embedded infirmware, such as an erasable programmable read-only memory (EPROM). Itwill be further appreciated that hardware modules may be comprised ofconnected logic units, such as gates and flip-flops, and/or may becomprised of programmable units, such as programmable gate arrays,application specific integrated circuits, and/or processors. The modulesdescribed herein are preferably implemented as software modules, but maybe represented in hardware and/or firmware. Moreover, although in someembodiments a module may be separately compiled, in other embodiments amodule may represent a subset of instructions of a separately compiledprogram, and may not have an interface available to other logicalprogram units.

In certain embodiments, code modules may be implemented and/or stored inany type of computer-readable medium or other computer storage device.In some systems, data (and/or metadata) input to the system, datagenerated by the system, and/or data used by the system can be stored inany type of computer data repository, such as a relational databaseand/or flat file system. Any of the systems, methods, and processesdescribed herein may include an interface configured to permitinteraction with patients, health care practitioners, administrators,other systems, components, programs, and so forth.

A number of applications, publications, and external documents may beincorporated by reference herein. Any conflict or contradiction betweena statement in the body text of this specification and a statement inany of the incorporated documents is to be resolved in favor of thestatement in the body text.

Although described in the illustrative context of certain preferredembodiments and examples, it will be understood by those skilled in theart that the disclosure extends beyond the specifically describedembodiments to other alternative embodiments and/or uses and obviousmodifications and equivalents. Thus, it is intended that the scope ofthe claims which follow should not be limited by the particularembodiments described above.

1. An analyte detection and treatment dosing system comprising: a fluidtransport network configured to provide fluid communication with a bodyfluid in a patient through a patient end; a body fluid analyzeraccessible via the fluid transport network, the body fluid analyzerconfigured to measure a characteristic of at least one analyte in thebody fluid and determine a concentration of the at least one analytefrom the measured characteristic; at least one pump system coupled tothe fluid transport network, the pump system having a sampling mode inwhich the pump system is operable to withdraw a sample of bodily fluidfrom the patient end and transport said sample of bodily fluid towardthe body fluid analyzer, and an infusion mode in which the pump systemis operable to transport an infusion fluid to the patient; and atreatment dosing system in communication with the body fluid analyzer,said treatment dosing system including a treatment dosing protocolstored in a computer memory and configured to automatically determine arecommended dose of an infusion fluid configured to provide glycemiccontrol, wherein the treatment dosing system determines the recommendeddose based at least in part on the measured concentration of the analyteand the stored treatment dosing protocol, wherein the treatment dosingsystem is configured to: provide signals to a control system that isconfigured to vary the pump rate of the at least one pump system todeliver the recommended dose of the infusion fluid to the patient, andwherein the treatment dosing system is configured to provide signals toa control system to automatically and completely stop the delivery ofthe infusion fluid if the measured concentration of the analyte is belowa certain threshold.
 2. The analyte detection system of claim 1, whereinthe treatment pump is configured to deliver infusion substancecontinuously at a basal rate through the patient end.
 3. The analytedetection system of claim 1, wherein the treatment pump is configured todeliver the recommended dose of the infusion substance as a bolusinjection through the patient end.
 4. The analyte detection system ofclaim 1, wherein the treatment pump is configured to deliver theinfusion substance continuously at a basal rate combined withintermittent bolus injections of the recommended dose.
 5. The analytedetection system of claim 4, wherein a time interval between two bolusinjections is determined based at least in part on the recommended doseand the basal rate.
 6. The analyte detection system of claim 1, whereinthe treatment pump is configured to deliver the recommended dose of theinfusion substance to the patient through said patient end during theinfusion mode of the pump system.
 7. The analyte detection system ofclaim 1, wherein the body fluid analyzer comprises a spectroscopicanalyzer.
 8. The analyte detection system of claim 1, wherein the bodyfluid analyzer comprises an electro-chemical analyzer.
 9. The analytedetection system of claim 1, wherein said at least one analyte comprisesglucose.
 10. The analyte detection system of claim 1, wherein theinfusion, substance comprises a substance selected from the groupconsisting of insulin and dextrose.
 11. The analyte detection system ofclaim 1, wherein the pump unit is selected from a group consisting ofvolumetric pump, syringe pump, peristaltic pump, vacuum pump, electricalpump, mechanical pump or hydraulic pump.
 12. The analyte detectionsystem of claim 1, wherein the dosing protocol comprises a tightglycemic control protocol.
 13. The analyte detection system of claim 1,wherein the treatment dosing system is configured to access ameasurement database, calculate an average concentration of the analytebased on one or more determinations by the body fluid analyzer of theconcentration of the analyte and determine the recommended dose for theinfusion substance based on the average concentration of the analyte.14. The analyte detection system of claim 1, wherein the treatmentdosing system is configured to access a measurement database, calculatea rate of change in the concentration of the analyte and determine therecommended dose for the infusion fluid based on the rate of change inthe concentration of the analyte.
 15. The analyte detection system ofclaim 1, further comprising a user interface including a dosing graphicthat indicates information related to the recommended dose, an actualdose of the infusion substance, or both.
 16. The analyte detectionsystem of claim 15, wherein the user interface includes an input elementconfigured to accept user input, the user interface further configuredto adjust the actual dose of the infusion fluid based at least in parton the user input.
 17. The analyte detection system of claim 16, whereinthe user interface comprises a touchscreen display and the input elementcomprises a button on the touchscreen.
 18. An analyte detection andtreatment dosing system comprising: a fluid transport network configuredto provide fluid communication with a body fluid in a patient through apatient end; at least one pump system coupled to the fluid transportnetwork, the pump system having a sampling mode in which the pump systemis operable to withdraw a sample of bodily fluid from the patient endand transport said sample of bodily fluid towards the body fluidanalyzer, and an infusion mode in which the pump system is operable totransport an infusion fluid to the patient; a body fluid analyzeraccessible via the fluid transport network, the body fluid analyzerconfigured to measure a characteristic of at least one analyte in thebody fluid and determine the concentration of the at least one analytefrom the measured characteristic; and a treatment dosing system incommunication with the body fluid analyzer, said treatment dosing systemincluding a treatment dosing protocol stored in a computer memory andconfigured to automatically determine a recommended dose of an infusionsubstance configured to provide glycemic control, wherein therecommended dose is determined based at least in part on one or moredeterminations by the body fluid analyzer of the concentration of theanalyte and the treatment dosing protocol, the treatment dosing systemcomprising a basal delivery system and a bolus injection system, bothsystems configured to deliver infusion substances to the patient throughsaid patient end and through the same intravenous access line, whereinthe treatment dosing system is configured to provide signals to acontrol system to automatically stop the delivery of the infusion fluidif the concentration of the analyte falls below a threshold or if atrend in the concentration of the analyte indicates that theconcentration will soon fall below the threshold.
 19. The analytedetection system of claim 18, wherein the basal delivery system isconfigured to deliver infusion substance continuously at a basal ratethrough the patient end.
 20. The analyte detection system of claim 18,wherein the bolus injection system is configured to deliver therecommended dose of the infusion substance as a bolus injection throughthe patient end.
 21. The analyte detection system of claim 18, whereinthe basal delivery system and the bolus injection system are controlledby a single treatment pump having a variable pump rate.
 22. The analytedetection system of claim 18, wherein the basal delivery system and thebolus injection system have separate pumps, but each pump cooperates toinfuse through the same intravenous access line.
 23. An analytedetection and control system to determine and regulate the concentrationof one or more analytes in a sample of bodily fluid, the systemcomprising: a control system; an analyte detector configured to measurea characteristic of at least one analyte in the sample of bodily fluidand determine a concentration of the analyte in the sample based on themeasured characteristic; a fluid handling system operatively coupled tothe analyte detector, said fluid handling system comprising a fluidpassageway in communication with a patient through a patient end; a pumpunit configured to engage the fluid handling system and draw a sample ofbodily fluid from the patient periodically at draw intervals of lessthan 1 hour for analysis; a source of infusion fluid configured toadjust glycemic levels in the patient, said infusion fluid source influid communication with the fluid handling system; and a treatmentdosing system in communication with the body fluid analyzer, saidtreatment dosing system including a treatment dosing protocol andconfigured to determine a recommended dose for the infusion fluid,wherein the recommended dose is determined based at least in part on oneor more determinations by the body fluid analyzer of the concentrationof the analyte and the treatment dosing protocol, wherein the controlsystem is configured to automatically stop the flow of the infusionfluid if one or more of the following conditions are met: the body fluidanalyzer determines that the concentration of the analyte is below acertain level; and the body fluid analyzer determines that theconcentration of the analyte is changing over time such that a fallbelow the level is imminent.
 24. The system of claim 23, wherein theinfusion fluid comprises glucose or Dextrose.
 25. The analyte detectionand control system of claim 23, wherein the infusion fluid comprisesinsulin.
 26. The analyte detection and control system of claim 23configured to draw a sample of bodily fluid at draw intervals of 45minutes or less.
 27. The analyte detection and control system of claim23 configured to draw a sample of bodily fluid at draw intervals of 30minutes or less.
 28. The analyte detection and control system of claim23 configured to draw a sample of bodily fluid at draw intervals of 15minutes or less.
 29. The analyte detection and control system of claim23, wherein the infusion source is located within a short distance ofthe patient to allow infusion of the infusion fluid at intervals of lessthan the draw intervals.
 30. The analyte detection and control system ofclaim 23, wherein the infusion source is located within a short fluiddistance of the site where the patient end of the fluid passagewayinterfaces with the patient.
 31. The analyte detection and controlsystem of claim 23, wherein the infusion source delivers infusion fluidto the patient within 1 minute of receiving an instruction from thecontrol system.
 32. The analyte detection and control system of claim23, wherein the infusion source delivers infusion fluid to the patientwithin 1-5 minutes of receiving an instruction from the control system.33. The analyte detection and control system of claim 23, wherein theinfusion source delivers infusion fluid to the patient within 1-10minutes of receiving an instruction from the control system.
 34. Ananalyte detection and treatment dosing system comprising: a fluidtransport network configured to provide fluid communication with a bodyfluid in a patient; a body fluid analyzer accessible via the fluidtransport network, the body fluid analyzer configured to measure acharacteristic of at least one analyte in the body fluid and determinethe concentration of the at least one analyte from the measuredcharacteristic; a treatment dosing system in communication with the bodyfluid analyzer, said treatment dosing system including a treatmentdosing protocol and configured to determine a recommended dose for aninfusion fluid configured to provide glycemic control, wherein therecommended dose is determined based at least in part on one or moredeterminations by the body fluid analyzer of the concentration of theanalyte and the treatment dosing protocol; a treatment pump coupled tothe fluid transport network, the treatment pump operable to transportthe infusion fluid to the patient through the patient end; and a fluidsystem controller comprising a graphic user interface, said fluid systemcontroller configured to actuate the treatment pump, shut-off thetreatment pump if the concentration of the at least one analyte is belowa certain level and control the pump rate of the treatment pump; whereinthe fluid system controller and the body fluid analyzer are bothincluded within a single housing, the graphic user interface is locatedon the same housing, and the graphic user interface is configured todisplay the determined analyte concentration and the recommended dose.35. The system of claim 34, wherein the graphic user interface includesan input element configured to accept user input, the user interfacefurther configured to adjust the actual dose of the infusion fluid basedat least in part on the user input.
 36. The system of claim 35, whereinthe graphic user interface is configured to display both the recommendeddose and the actual dose, where both the recommended dose and the actualdose are expressed as infusion rates.
 37. The system of claim 34,wherein the graphic user interface includes an input element configuredto accept user input, the user interface configured to actuate the pumpunit based at least in part on the user input.
 38. An analyte monitoringsystem comprising: a fluidic system in fluid communication with a sourceof bodily fluid, said fluidic system being configured to obtain a firstsample of bodily fluid from the source at a first time; an analytedetection system configured to analyze the first sample of bodily fluidor a component of the first sample of bodily fluid; a treatment dosingsystem; and a fluid infusion system; wherein the analyte detectionsystem is configured to determine the concentration of an analyte insaid first sample of the bodily fluid or a component of the first sampleof the bodily fluid and store the value of the determined concentrationin a measurement database, wherein the fluidic system further obtains asecond sample of the bodily fluid at a second time and presents saidsecond sample to the analyte detection system for analysis, wherein theanalyte detection system analyzes the second sample or a component ofthe second sample and determines the concentration of the analyte in thesecond sample or the component of the second sample, wherein thetreatment dosing system calculates a rate of change of the concentrationof the analyte, and wherein the treatment dosing system communicateswith the fluid infusion system to stop the flow of an infusion substanceif: concentration of the analyte in the first or second sample is belowa certain threshold; or the rate of change of the concentration of theanalyte is below a certain prescribed value and the concentration of theanalyte in the first or second sample is close to the threshold.